At January 2009 Issue

THE COMPOSITE SIGNAL APPROACH IN STOCKS

P. 22

BEAR NECESSITIES: Understanding stock behavior in down markets p. 14

ZONING IN ON IPO opportunities p. 58

SCALPING: Trading the tape, not the chart p. 28

VOLATILITY and swap spreads p. 42

SYSTEM LAB: Testing the double repo p. 46

THIS, TOO, SHALL PASS (but when?)

$4.95

Printed in the U.S.A.

www.activetradermag.com

CONTENTS January 2009 • VOLUME 10, 10, NO. 1

®

TRADING STRATEGIES FOR THE FINANCIAL MARKETS

8

Market Pulse The bear and bull face-off Understanding the stark differences between how the market moves in bull and bear periods can help you navigate this tough market. By David Bukey

Trading Strategies

15

Combine and conquer: Testing a consensus approach A recent academic study explains how trading rules from multiple strategies can be combined to create more effective signals. By Camillo Lento

19

Scalping: Playing the lean Leave your technical tools at the door — scalping is about flipping, fake-outs, and other tricks of the trade. Scalpers need to approach the market with a different mindset than the typical technical trader. By John Grady

24

Developing a trading system Active Trader kicks

off a year-long series of articles on system

development by mapping out a game plan for the coming months. By Active Trader Staff

In every issue…

57 Global Marketplace International market performance. performance.

3 Editor’s Note 4 Contributors 5 Opening Trades Trends and events moving the markets.

1

59 ETF Snapshot Volume, volatility, and momentum statistics for exchange-traded exchange-traded funds.

60 Stock & Futures

63 Key Concepts 65 Trading Resources New products, services, and books.

69 Trading Calendar 71 Upcoming Events

Snapshots Volume, volatility, and momentum statistics for futures and stocks. www.activetradermag.com • January 2009 • ACTIVE TRADER

Contents continued Contact Active Trader: Editorial inquiries: [email protected]

25

Are options alternative ownership? Maybe not A series of experiments show how options stack up to positions in the underlying

Comments, suggestions: [email protected] For advertising or subscription information, log on to: www.activetradermag.com

market.

Inside the Market

By Keith Schap

47

Stagnant IPO, ETF listings reflect battered market A lack of new companies going public speaks volumes about the current market condition, but a new study shows IPOs that survive a bad environment may be stronger in the long run. By Chris Peters

Advanced Strategies

31

Other stories:

Volatility and swap spreads

Carbon trading surge • Gold’s perplexing

The relationship between swap spreads,

performance • Hedge-fund industry

the yield curve, and the term structure of

woes • Central Central banks slash slash rates •

fixed-income volatility offers valuable

Global numbers

insights into the direction of corporate

The Economy

bonds and stocks. By Howard L. Simons

61

U.S. economic briefing Updates on economic numbers and

Trading System Lab

35

the market’s reaction to them.

Double-repo systems

Technology for Traders

This approach waits for the double penetration of a forward-adjusted moving

68

average following a price thrust.

Web Watch: Watch: Collective2.com Collective2.com A community-based Web site tracks

By Volker Knapp

thousands of trading systems and matches traders with system developers.

The Face of Trading

41

42

Twists and turns

Trade Diary

By Active Trader staff

72

Taking a gamble on a banking stock.

Q&A

73

Taking

Ken Grant on risk

quick profits

Risk management expert Ken Grant

and maintaining

discusses the current turmoil and the

tight stops.

potential toll hedge-fund pullouts could take on the market. By Mark Etzkorn

2

www.activetradermag.com • January 2009 • ACTIVE TRADER

Editor’s NOTE

This, too, shall pass…eventually

A

s the level of hyperbole in financial media commentary exceeds the level of market volatility itself, keep something in mind: Nobody has a clue what’s going to happen. Not Warren Buffet, not George Soros, not the guy next to you on the train, and certainly not any of us in the press or the people who share their thoughts with us. People who claim they do are liars or delusional. We We all have access to the same information, although many people choose to ignore it. The most logical, best-educated guesses would extrapolate from similar episodes in the past, adjust for the present situation’s unique qualities, and provide a wide margin of error. Fat lot of good that will do you. The margin of error would account for outcomes so disparate as to make any course of implied action in the market woefully limited — and risky. Even if that weren’t the case, logic is of only limited use in this situation, as it is an entirely psychological, emotion-driven phenomenon. There really are few historical parallels to the current situation, other than those that fall under the general banner of “Panic.” And aside from the observation that panics tend to be buying opportunities — in the long-term — there’s not a lot to say. “Tend to be” is a dicey concept on which to hang your financial future. After all, the market lost a hair less than 50 percent from high to low in the initial 1929 crash. More money was destroyed when the market subsequently rallied 52 percent and then — between April 1930 and July 1932 — shed 86 percent of its value. The U.S. stock market has now lost nearly half its value for the second time 3

in less than a decade. This wasn’t supposed to happen; 2000-2002 was supposed to be the big flush-out. The speed and severity of this drop makes the previous bear market look like an orderly correction. Which is perhaps why we shouldn’t

As people lose their capacity to be shocked and return their attention to the mundane tasks of everyday life, the day draws nearer when we will be able to say a bottom is in. hope for a quick, massive rebound (right now that certainly doesn’t seem to be an issue). It would simply be a sign the market hasn’t exorcised its demons. That’s what you call a catch-22, because if it’s unhealthy for the market to rally robustly right now, that means the preferable alternative is for it to hang around the October lows or even move lower — and continue to erode stomach linings and inflame blood vessels in the process. And with hedge-f und liquidations still underway and a likely spike in unemployment in our future, there’s plenty of room for another downdraft.

But our culture’s famously short attention span could come in quite handy in the months to come. People are already showing signs of becoming numb to the onslaught of negative news. The media will eventually tire of the story, and could be helped in this regard by the distraction of a new president. As people lose their capacity to be shocked, reconcile themselves to their trimmed-down balance statements, and return their attention to the mundane tasks of everyday life, the day draws nearer when — in retrospect, of course — we will be able to say with some confidence that “a bottom is in.” (The other thing that might help is publicly beheading the financial masters of the universe who helped get us where we are, and the government that decided we should foot the bill for them, but let’s not hold our breath.) One day, things will be different. Just don’t ask me or anyone else when, exactly. In “Ken Grant on risk” (p. 42) the long-time risk-management expert notes, “One of the things that separates the real pros from the wannabes is the pros know bad markets — and good markets, for that matter — don’t last forever, and they plan accordingly.” I will make a bold forecast: 15 years from now, the S&P 500 index will be higher than it is today (Nov. 12, 2008). Now I feel terrible, though, because any time I make this kind of prediction, I’m almost always wrong. But then, I have plenty of company.

Mark Etzkorn, Editor-in-chief Editor-in-chief


• January

2009

• ACTIVE TRADER

This Month’s ®

For all subscriber services: Active Trader Magazine P.O. Box 567 Mt. Morris, IL 61054-0567 • (800) 341-9384 • www.activetradermag.com

Editor-in-chief:

Mark Etzkorn [email protected]

Managing editor:

Molly Goad [email protected]

CONTRIBUTORS

Howard Simons is president of Rosewood Trading Inc. and a

strategist for Bianco Research. He writes and speaks frequently on a wide range of economic and financial market issues.

Keith Schap is a freelance writer specializing in risk management

and trading strategies. He is the author of numerous articles and several books on these subjects, including The Complete Guide to Spread

Trading (McGraw-Hill, 2005). He was a senior editor at Futures magazine and senior technical marketing writer at the CBOT.

Senior editor:

David Bukey [email protected]

Asso Associ ciat ate e edit editor or::

Chris Peters [email protected]

Contributing writers:

Camillo Lento is a lecturer in the accounting department at Lakehead University

in Thunder Bay, Ontario, Canada. Before joining the faculty of business administration, Lento obtained his Chartered Accountant (Ontario) Designation, while in senior

Thom Hartle, Howard L. Simons, Marc Chandler, Keith Schap, Robert A. Green

positions in accounting, auditing, and business valuations. He holds a master’s degree

Editorial assistant and Webmaster:

and finance) from Lakehead University, and has marked non-comprehensive simula-

Kesha Green Art Art dir directo ector: r:

Laura Coyle [email protected]

in management and an honors bachelor’s of commerce degree (majors in accounting tions at the ICAO’s School of Accountancy. Lento has various publications in journals such as the Journal of Applied Business Research Research and Applied Economics Letters Letters , and has presented original research at many international conferences.

President:

Phil Dorman [email protected]

Publisher, Ad sale sales s East East Coas Coastt and and Midw Midwes est: t:

Bob Dorman [email protected]

John Grady first learned the art of scalping while trading futures

for a proprietary trading firm in Chicago. It was there he discovered the importance of reading the order book and realized technical analy-

Ad sale sales s West Coast and Southwest only:

sis is typically more of a hindrance than a help in day trading. trading. He is

Alli Allison son Chee Chee

the author of No B.S. Day Trading and currently trades from his home

[email protected]

Classified ad sales:

Mark Seger

in southern Florida. For more scalping strategies and information on how to read the order book, visit www.NoBSDayT www.NoBSDayTrading.com. rading.com.

[email protected]

Volker Knapp has been a trader, system developer, and researcher Volume 10, Issue 1 Active Trader is published monthly by TechInfo, Inc., 161 N. Clark Street, Suite 4915, Chicago, IL 60601. Copyright © 2008 TechInfo, Inc. All rights reserved. Information in this publication may not be stored or reproduced in any form without written permission from the publisher. Annual subscription rate is $59.40. The information in Active Trader magazine is intended for educational purposes only. It is not meant to recommend, promote or in any way imply the effective- ness of any trading system, strategy or approach. Traders are advised to do their own research and testing to determine the validity of a trading idea. Trading and investing carry a high level of risk. Past performance does not guarantee future results. 4

for more than 20 years. His diverse background encompasses positions such as German National Hockey team player, coach of the Malaysian National Hockey team, and president of VTAD (the German branch of the International Federation of Technical Analysts). In 2001 he became a partner in Wealth-Lab Inc. (www.wealth-lab.com), which he still runs.


OPENING Trades

Stocks lurch around October lows After testing the Oct. 10 panic low later in the month, the U.S. stock market staged a pre-presidential election rally early in November — only to turn back down the day after Sen. Barack Obama was elected the 44th President of the United States on Nov. 4.

Index

Oct. 10 low

Oct. 24-28 low

S&P 500 (SPX)

839.8

845.27 1,007.51 919.21

Nasdaq 100 (NDX) Russell 2000 (RUT)

Nov. 4 high

1,196.11 1,149.12 1382.65 467.92

441.92

551.02

Nov. 10 close

Max. YTD decline (thru 11-10)

-42.80%

1,251

-44.88%

493.27

-42.31%

Dow Industria Industrials ls (DJIA) 7,884.82 8,143.59 9,653.95 8,870.54 -40.56%

S&P 500 median daily moves Daily range

One-day closing change

10/10/0811/10/08

10/11/0410/9/08

Ratio

10/10/08- 10/11/04- 11/10/08 10/9/08 Ratio

49.77

11.95

4.16

3.13%

0.47%

6.64

The Nasdaq 100 and Russell 200 indices actually made lower lows in late October, while the S&P 500 and the Dow made slightly higher lows. All the indices rallied briskly through Nov. 4 before putting in a huge post-election day loss. Nonetheless, as of Nov. 10, the S&P was around 9 percent above its Oct. 10 low.

Voices in the market: “

I made a mistake in presuming the

Virtually every day has been an exercise in chest-clutching. The median S&P daily range of 49.77 points between Oct. 10 and Nov. 10 is more than four times the median of the preceding four years, and the median close-to-close change is more than six times larger. The market has matched the former Source: TradeStation volatility level only twice (1987 and 1998) in the past 25 years, and has not reached the latter level in the past quarter century. The market’s volatility is a sign it is not yet out of the woods, and its reduced volume leaves it susceptible to continued thrashing. “Ken Grant on risk” (p. 42) addresses some of the challenges the market faces in the near future and the signs that may indicate it has found its bottom.

Sector ETF picture There were, perhaps surprisingly, a handful of areas that managed to post gains in the month after the initial October lows, mostly in the fixed-income arena. The iShares California Muni Bond fund (CMF) was hot, but not particularly liquid. Other top-returning exchange-traded funds (ETFs) included dividendyielding, energy, energy, and biotech funds. “Stagnant IPO, ETF listings reflect battered market” (p. 47) looks at the state of the ETF market.

ETF

S y m

20- 20- day 11/10 r etur n on clos lose 11/10

60- day day avg. daily volume

iShares S&P California Muni Bond

CM F

102.99 12.07%

6,088

WisdomTree Earnings Top 100 Fd.

EE Z

28.11

7.62%

10,654

Vanguard Intermediate-Term Bond

BIV

71.99

5.60%

59,328

self-interest of organizations, specifi-

Vanguard Short-Term Bond ETF

BSV

76.34

5.20%

138,097

cally banks and others, was such

iShares Lehman Aggregate Bond Fd. AGG

95.91

5.06%

688,141

that they were best best capable of pro- pro-

Europe 2001 HOLDRS

E KH

47.14

3.83%

1,078

Biotech HOLDRS

B BH

173.11 3.66%

iShares DJ US Oil & Gas

IEO

42.29

3 .4 2 %

1,030,815

Market Vectors-Gaming ETF

BJK

16.70

3.09%

2,559

SPDR Lehman Intl Treasury Bond

B WX

49.20

3.04%

138,722

tecting their own shareholders.

”

— Alan Greenspan, speaking before Congress in October.

5


• January

2009

199,549

• ACTIVE TRADER


He underestimated the self interest of people — their

own self interest. They’re the greediest people on earth. How can you underestimate them?

”

--Radio personality Steve Dahl, on Greenspan’s comment

Source: eSignal

Metals swing to new lows Crude falls below $60 Crude oil dropped below $60 in early November. Despite OPEC’s intended output cutback for November, December crude (CLZ08) hit a 22month low of $59.97 on Nov. 7, 60 percent below its all-time peak in July. July. December natural gas (NGZ08), heating oil (HOZ08), and gasoline (RBZ08) also breached psychological barriers in October. Natural gas broke through $7.00 and fell as low as $6.24. Heating oil futures dropped below $2.00 in late October before bouncing as high as $2.20 in early November, while gasoline futures traded near $1.40.

Source: eSignal

December gold futures (GCZ08) fell 18.5 percent in October, dipping briefly below $700. After touching a 21-month low of $681 on Oct. 24, gold jumped 10 percent to trade at $750 by Nov. 10. December silver (SIZ08) dropped 21 percent in October, part of a three-month, 46-percent drop to a multi-year low of $8.40 on Oct. 28. By Nov. 4, however, the market bounced back to $10. December copper (HGZ08) dropped 36 percent in October, falling below $175 several times. After a short bounce back above $200, copper slipped to $169.70 by Nov. 7.

Who says the dollar is dead? The U.S. dollar was one of the few clear beneficiaries of the financial meltdown, as it proved — despite America’s flagging international reputation reputation in recent years and the advent advent of Asian economic superpowsuperpowers — that it is still a safe-haven in times of trouble. The U.S. dollar index pulled back slightly in early November after capping its biggest rally in more than seven years with a two-and-half-year high in October. Source: TradeStation

Treasuries reach new highs After hitting a six-month high on Sept. Sept. 16, December December 10-year T-note T-note futures (TYZ08) (TYZ08) fell 6.2 percent percent by Oct. 14, the largest monthly decline in five years. But the 10-year rebounded quickly, climbing 3.5 percent in less than two weeks. By Nov. 10, the market had dropped to 115 21/32. Meanwhile, shorter-term Treasury futures hit multi-year highs. December 5-year T-note futures (FVZ08) jumped 2.4 percent percent in the first week of November November to a five-year high of 116. December December 2-year T-note T-note futures (TUZ08) followed a similar trajectory. ACTIVE TRADER • January

2009

•


Source: eSignal

6

Opening Trades continued


I was in this game for the money. The low hanging fruit, i.e., idiots whose parents paid for prep

school, Yale, and then the Harvard MBA, was there for the taking. These people who were (often) truly not worthy of the education they received (or supposedly received) rose to the top of companies such as AIG, Bear Stearns, and Lehman Brothers and all levels of our government. All of this behavior supporting the Aristocracy only ended up making it easier for me to find people stupid enough to take the other side of my trades. God bless America.

”

— Hedge-fund manager Andrew Lahde of Lahde Capital, in a letter announcing the dissolution of his very profitable hedgefund and his retirement from the industry.

Grains stabilize, softs weaken Grain futures dropped in early October, and then traded flat for the remainder of the month. December corn (CZ08) fell to a 21-month low on Oct. 16 before trading in a $0.50 range through Nov. 10. Soybeans, wheat, and soybean products made similar moves, dropping to multi-month lows before stabilizing. January rough rice (RRF09) (RRF09) ended a four-week four-week fall of 29 percent percent to $14.61 on Oct. 27, 27, and then bounced nearly 10 percent by Nov. 5. Cocoa futures slid 20 percent in October and traded 43 percent below its July all-time high. After hitting a 14-month low on Oct. 24, December cocoa futures (CCZ08) jumped 17.6 percent in the next three days, but then continued to fall in the first part of November. December cotton (CTZ08) fell 23 percent in October after falling 18 percent in September. Cotton then slipped another 5 percent in the first week of November. December coffee (KCZ08) dropped 12 percent in the first five days of October, rebounded slightly, and eventually hit a 17-month low of $105.05 on Oct. 27.

Source for all charts: eSignal

Livestock futures avoid slaughter October was a tough month for livestock futures. December live cattle (LCZ08) dropped 13.22 percent from Sept. 30 to Oct. 24, and December lean hogs (LHZ08) fell 8.9 percent during the same period. However, December live cattle began to rebound in late October and early November as December lean hogs continued to slip. By Nov. 10, live cattle climbed 7.4 percent from the six-month low it hit on Oct. 24. But lean hogs fell an additional 6.5 percent.

Porsche beats hedge funds to finish line Iconic car marker Porsche cashed in after revealing it controlled a majority stake in Volkswagen AG, causing VW shares to jump nearly 500 percent within a few days. Porsche secretly built a 74.1-percent investment in VW with cash-settled options, meaning that most shares were tied up and unavailable to other investors. When the news broke broke on Oct. 26, short sellers of VW stock struggled struggled to find shares to buy back, and and the stock surged 376 percent to €1,005, causing VW to briefly become the most valuable firm in the world. As a result, several prominent U.S. hedge funds lost money, including Steve Cohen’s SAC Capital and David Einhorn’s Greenlight Capital. German regulators are investigating whether VW stock was manipulated, but Porsche has not been charged with wrongdoing. 7


• January

2009

• ACTIVE TRADER

MARKET Pulse

The bear and bull face-off Examining how recent bull and bear periods influenced the stock market’s short-term price behavior.

BY DAVID BUKEY

W

ith nearly all stock markets mired in official bear territory, many traders are trying to make money by selling short. This seemed incredibly compelling when the Dow Jones Industrial Average plunged 27.35 percent in the first eight days in October alone. But the immediate 20-percent rebound within three days likely scarred many short sellers who entered toward the end of the Dow’s initial drop. Trading stocks from the short side is virtually always more

FIGURE 1: BEAR MARKET, 2000-2003

difficult than trading from the long side. Statistics show market volatility spikes when prices drop, making it a more challenging environment in which to earn profits. The first step in developing an approach tailored for a down market is to measure the market’s typical price behavior during bearish conditions. “Bull vs. Bear: The details matter” ( Active Trader , November 2002) compared the S&P 500 tracking stock’s (SPY) daily price characteristics in bull and bear markets: 1998 to 2000 vs. 2000 to 2002, respectively. Here, we take a look at SPY’s short-term behavior during more recent bullish and bearish periods, focusing on differences in its daily ranges, close-to-close moves, and price runs of different lengths and sizes.

Bull vs. bear showdown Let’s compare SPY’ S PY’s price behavior in two distinct periods: the bear market from March 1, 2000 to Feb. 28, 2003 and the bull market from March 3, 2003 to Feb. 28, 2006. Figure 1 shows a daily SPY chart during the bear phase as it dropped 38.7 percent within three years, a very volatile period that resembles 2008’s price action. Figure 2 shows SPY during the study’s bull peri-

KC

The S&P 500 tracking stock (SPY) fell 38.7 percent from March 1, 2000 to Feb. 28, 2003 – a very volatile period that resembles price action in 2008. Source: eSignal

8

For more information about the following concepts, go to “Key concepts” on p. 63.

• Average and median


FIGURE 2: BULL MARKET, 2003-2006

od, in which it gained 34.8 percent from March 2003 to March 2006. The market’s long-term trend is clear in both figures. However, SPY rebounded sharply on several occasions before resuming the prevailing downturn in Figure 1. And the market hit many rough patches during its overall rally in Figure 2, including a prolonged flat period in 2004. Clearly, Clearly, traders could have made money on either side of the market in both periods. Let’s compare general market characteristics between both periods on a day-to-day basis.

SPY rallied 34.8 percent from March 3, 2003 to Feb. 28, 2006, although it traded sideways in much of 2004. Source: eSignal

and bear markets. The first three columns list SPY’s close-toclose move, its largest up move (LUM, close to next day’s high),

Bear markets are choppy Table 1 compares SPY’s average and median daily moves in bull

continued on p. 1 0

TABLE 1: BEAR AND BULL DAILY STATISTICS

Closeto-close

LUM

LDM

Overnight move

Open to high

Open to low

Open to close

Daily range Daily as % of range ($) midpoint

March 2000 to March 2003

Avg: Med: Pct. > 0:

-0.05%

0.97%

-1.10%

-0.01%

0.93%

-1.02%

-0.04%

2.24

1.96%

-0.05%

0.75%

-0.87%

0.00%

0.73%

-0.84%

-0.05%

2.02

1.74%

March 2003 to March 2006

Avg: Med: Pct. > 0:

0.06%

0.59%

-0.52%

0.04%

0.53%

-0.53%

0.02%

1.16

1.06%

0.09%

0.49%

-0.40%

0.04%

0.43%

-0.41%

0.06%

1.08

0.95%

48.74%

49.40%

56.03%

48.60%

55.10%

53.25%

The market’s intraday moves were roughly twice as volatile during the last bear market (2000-2003) than during the subsequent bull market (2003-2006).

TABLE 2: BEAR AND BULL OPENING GAPS Drop below yesterday’s low

Rise above yesterday’s high

Inside days

Outside days

Opening gap up

Opening gaps* Opening gap Opening up gap filled down

Opening gap down filled

Bear market - March 2000 to March 2003

51.80%

46.87%

10.25%

9.45%

42.21%

35.21%

42.88%

68.32%

Bull market - March 2003 to March 2006

43.97%

54.04%

13.64%

12.05%

41.93%

65.30%

31.08%

68.51%

* opening gap >= .1% of yesterday's close

Opening gaps up were more likely to be filled in bull markets than bear markets. But opening gaps down were filled 68 percent of the time, regardless of market conditions.

ACTIVE TRADER • January 2009 • www.activetradermag.com

9

Market Pulse continued FIGURE 3: BEAR MARKET DAILY RANGES

and its largest down move (LDM, close to next day’s low). The middle columns show SPY’s overnight and intraday moves — open to high, open to low, and open to close. The last two columns list SPY’s daily (high-low) range and its daily range as a percentage of each day’s midpoint. Finally, the percentage of gains (Pct. > 0) is shown for several periods. From a directional standpoint, there are no dramatic differences between the bull and bear markets. Obviously, the market was skewed toward losses during the bear market and tended to post small gains in the bull market. But Table 1’s

SPY was much more volatile in the bear market, with a typical daily range between $1.00 to $3.00. The largest number of high-low moves fell in the $1.51 to $2.00 range. FIGURE 4: BULL MARKET DAILY RANGES

SPY was twice as volatile during the bear market. real news is that SPY was twice as volatile during the bear market. For example, the median bear-market LUMs and LDMs are 0.75 percent and -0.87 percent, respectively, respectively, while their bull-market counterparts are just half as large (0.49 percent and -0.40 percent). The same dynamic appears in SPY’s open-to-high and open-to-low moves. Moreover, Moreover, SPY’s daily range is twice as large during the bear period than during the subsequent bull period. Table 2 (p. 9) compares how often SPY formed various one-day patterns in bull and bear markets. The patterns that stick out are opening gaps, which form when the market opens above or below yesterday’s close. For example, when SPY gapped higher at the open, the market was more likely to drop back to its opening price, “filling” that gap, in a bull market, which seems counterintuitive. And after forming an opening gap down, SPY 10

SPY was much less volatile in the bull market; the majority of its moves ranged between $0.50 to $1.50, well below the typical bear market daily range.

TABLE 3: DAILY UP MOVES Bear (752 days)

# of times: % of times: Bull (755 days)

# of times: % of times:

HH

HL

HC

HH+HC

HH+HL+HC

352 46.81%

360 47.87%

366 48.67%

248 32.98%

212 28.19%

HH

HL

HC

HH+HC

HH+HL+HC

407 53.91%

418 55.36%

422 55.89%

329 43.58%

263 34.83%

SPY reached fewer higher highs, higher lows, and higher closes during the bear market of 2000 to 2003 than during the subsequent bull market of 2003 to 2006.


FIGURE 5: BEAR MARKET CLOSE-TO-CLOSE MOVES

climbed back to its opening price 68 percent of the time, regardless of market conditions.

Daily ranges and close-to-close close-to-close differences

The majority of SPY’s close-to-close moves ranged from $0.01 to $1.50 in the bear period, while less than 25 percent of its moves exceeded $1.00 in the bull period (Figure 6).

Table 1 shows SPY formed larger daily ranges in the bear market. Figure 3 shows the distribution of absolute values for the daily ranges in the bear market period. Figure 4 shows the same statistics

The market tended to drop sharply after

FIGURE 6: BULL MARKET CLOSE-TO-CLOSE MOVES

hitting new five-day highs in bear markets, but the counter-rallies can be surprisingly strong.

More than half of SPY’s close-to-close moves were less than $0.51 in the bull period.

TABLE 4: DAILY DOWN MOVES Bear (752 days)

# of times: % of times: Bull (755 days)

# of times: % of times:

LH

LL

LC

LL+LC

LL+LH+LC

389 51.73%

396 52.66%

385 51.20%

273 36.30%

238 31.65%

LH

LL

LC

LL+LC

LL+LH+LC

332 43.97%

344 45.56%

323 42.78%

236 31.26%

187 24.77%

SPY formed lower highs, lower lows, and lower closes more often during the bear market than during the bull period.

for the subsequent bull market. The differences are striking. The majority of bear-market daily ranges are between $1.01 and $3, peaking from $1.51 to $2. By contrast, most bull-market daily ranges are between $0.51 and $1.50, culminating from $0.51 to $1. The average bear-market range was $2.24 vs. just $1.16 in the bull period. Figures 5 and 6 show the same type of distributions of close-to-close differences in the bear and bull markets, respectively. In the bear market, roughly 75 percent of all close-to-close differences were $0.51 or larger. In the bull market, however, only about half of them fell into that category. continued on p. 1 2


11

Market Pulse continued

TABLE 5: BEAR MARKET CONSECUTIVE HIGHS

# of times: % of times: Average move: Median move:

Consecutive HCs 2 3 4

5

6

7

170 22.61% 2.33% 1.99%

11 1.46% 4.14% 3.58%

5 0.66% 4.00% 3.98%

2 0.27% 4.36% 4.36%

72 9.57% 3.49% 3.03%

31 4.12% 4.54% 4.50%

Tracking uptrends and downtrends

One way to define an uptrend is to look for a string of consecutive higher highs, higher lows, and higher closes. Downtrends would contain strings of Consecutive HHs+HCs back-to-back lower lows, lower highs, and lower 2 3 4 5 6 closes. # of times: 98 37 12 2 1 In theory, the market would seem more likely to % of times: 13.03% 4.92% 1.60% 0.27% 0.13% form a series of consecutive highs in bull markets Average move: 2.73% 4.09% 5.94% 3.46% 3.98% and a string of consecutive lows in bear markets. Median mo move: 2.34% 3.45% 5.69% 3.46% 3.98% Nonetheless, Figures 1 and 2 show that SPY’s longer-term trends were broken up by frequent sellConsecutive HHs+HLs+HCs offs and counter-rallies. 2 3 4 Table 3 (p. 10) compares the number of times # of times: 75 23 5 SPY formed consecutive higher highs, higher lows, % of times: 9.97% 3.06% 0.66% and higher closes in bull and bear markets. The Average move: 2.75% 4.39% 7.20% Median move: 2.35% 3.83% 7.13% table also shows the number of combinations of higher highs and higher closes (HH+HC) and highThe market closed higher up to seven days in a row in the bear er highs, higher lows, and higher closes market of 2000 to 2003. However, strings of higher highs and higher (HH+HL+HC) in each period. closes formed less often and were shorter in length. The market clearly reached more highs during the bull market than the bear market, which is TABLE 6: BULL MARKET CONSECUTIVE HIGHS no surprise. SPY climbed to highConsecutive HCs er highs, higher lows, or higher 2 3 4 5 6 7 8 9 closes at least 54 percent of the # of times: 227 130 71 37 18 9 4 1 time in the bull period, and it % of of ti times: 30.07% 17.22% 9.40% 4.90% 2.38% 1.19% 0.53% 0.13% Average move: 1.14% 1.69% 2.44% 3.26% 4.04% 5.18% 6.24% 5.31% reached either of these milestones Median mo move: 1.07% 1.53% 2.14% 2.87% 3.31% 3.86% 4.98% 5.31% less than half the time in the bear period. Consecutive HHs+HCs Also, combinations of highs h ighs — 2 3 4 5 6 7 8 HH+HC and HH+HL+HC — # of times: 143 71 34 14 5 3 1 formed more often in the bull % of times: 18.94% 9.40% 4.50% 1.85% 0.66% 0.40% 0.13% period. For example, HH+HC pat Average move: 1.26% 1.87% 2.53% 3.69% 5.33% 6.37% 5.22% terns occurred 44 percent of the Median move: 1.18% 1.57% 2.21% 3.25% 3.86% 4.65% 5.22% time in the bull market vs. just 33 percent of the time in the bear Consecutive HHs+HLs+HCs market. And there is a similar, but 2 3 4 5 6 7 8 smaller, difference between # of times: 103 40 17 7 3 2 1 % of times: 13.64% 5.30% 2.25% 0.93% 0.40% 0.26% 0.13% HH+HL+HC patterns in those Average move: 1.29% 1.81% 2.25% 3.04% 3.65% 4.25% 5.22% periods. Median move: 1.26% 1.58% 2.04% 3.24% 3.82% 4.25% 5.22% Table 4 (p. 11) resembles Table 3, but lists the number of times The market closed higher up to nine consecutive days in the bull market of 2003 to SPY formed lower highs, lower 2006. Although there were longer strings of higher closes in the bull market, the mar- lows, and lower closes. As you ket tended to gain more ground during consecutive highs in the bear market (Table 5), might expect, consecutive lows another sign of increased volatility. volatility. were more common in the bear 12


TABLE 7: BEAR MARKET CONSECUTIVE LOWS

period. SPY hit lower highs, lower lows, or lower closes at least 51 percent of the time in the bear market, while it formed those patterns much less often in the bull market. The same dynamic applies to combinations of lows — LL+LC and LH+LL+LC patterns, which were more common in the bear market. By contrast, LH+LL+LC patterns occurred only 25 percent of the time in the bull market, the least frequent pattern in Tables 3 and 4.

# of times: % of of titimes: Average move: Median m ov ove:


Consecutive LCs 2 3 4

5

6

7

190 25.27% -2.37% -2.13%

11 1.46% -6.47% -5.72%

3 0.40% -5.97% -4.95%

1 0.13% -5.41% -5.41%

Consecutive LLs+LCs 2 3 4

5

6

120 15.96% -2.64% -2.39%

6 0.80% -7.05% -6.61%

1 0.13% -8.43% -8.43%

85 11.30% -3.62% -3.25%

46 6.12% -4.05% -3.52%

33 4.39% -4.96% -4.58%

14 1.86% -5.98% -5.32%

Consecutive LHs+LLs+LCs 2 3 4 5

Consecutive highs and lows

# of times: 91 33 8 3 Table 5 lists runs of consecutive daily SPY highs % of times: 12.10% 4.39% 1.06% 0.40% during the bear market from March 2000 to March Average move: -2.77% -4.20% -6.46% -6.50% 2003. The first section shows the number and perMedian move: -2.51% -3.54% -5.32% -6.28% centage of times the market made consecutive As expected, there were more consecutive lows in the bear market higher closes from two to seven days in a row. For than consecutive highs. example, SPY formed back-to-back higher closes 170 times (22.61 percent), and it made seven conclimbed just half as far when it formed the same patterns in the secutive higher closes only twice. To find the exact number of runs of a specific length, subtract the number of the next longest run from the length you are tryTABLE 8: BULL MARKET CONSECUTIVE LOWS ing to determine. For example, there were 31 cases of four conConsecutive LCs secutive higher closes, but those runs are already included in the 2 3 4 5 72 runs of three consecutive HCs. As a result, there were 41 # of times: 131 49 14 2 instances (72-31) of three consecutive HCs only. % of times: 17.35% 6.49% 1.85% 0.26% Table 5’s lower two sections show HH+HC and HH+HL+HC Average move: -1.20% -1.84% -2.18% -2.15% patterns of various lengths. For example, SPY formed up to six Median mo move: -1.03% -1.66% -1.95% -2.15% consecutive days of HHs and HCs, while it posted up to four days of back-to-back HHs, HLs, and HCs. The final two rows of Consecutive LLs+LCs each section show SPY’s average and median close-to-close 2 3 4 5 moves during each run. For example, the market jumped an # of times: 85 30 8 1 average 7.2 percent during its series of four consecutive % of times: 11.26% 3.97% 1.06% 0.13% Average move: -1.34% -1.91% -2.15% -1.53% HH+HL+HC days in the bear market. Median mo move: -1.24% -1.98% -1.64% -1.53% Table 6 is similar to Table Table 5, but it lists runs of consecutive

daily SPY highs during the bull market. If you compare Tables 5 and 6, you will notice several key differences between bearish and bullish environments. First, SPY formed longer strings of consecutive highs during the bull market — up to nine days of consecutive HCs and eight days of HH+HC and HH+HL+HC patterns. And those bullish patterns were more common in the bull market. In the bear market, however, SPY rose further during consecutive highs. For example, SPY jumped an average 2.33 percent during two back-to-back HC days in the bear market, but it continued on p.


Consecutive LHs+LLs+LCs 2 3 4


62 21 5 8.21% 2.78% 0.66% -1.43% -1.98% -2.36% -1.37% -1.76% -1.82%

SPY rarely formed consecutive lows in the bull market, and these down moves were roughly half as large as their bear market counterparts (Table 7).

14

13

Market Pulse continued

bull market. In short, bear-market uptrends were less common and shorter in length than their bull-market counterparts, but they were stronger, supporting the conclusion that SPY is more volatile during bear markets. Tables 7 (p. 13) and 8 list the number of consecutive daily SPY lows in bear and bull markets, respectively. respectively. SPY made longer strings of consecutive lows in the bear market — up to seven consecutive days of LCs vs. a maximum of five in the bull market. Also, patterns of consecutive lows were more common in the bear market, which is no surprise. Finally, SPY fell twice as far during bear-market patterns, compared to their bull-market equivalents.

Selling short-term highs This study shows SPY has been more volatile in bear markets than in bull markets, a fact that is obvious to anyone who has traded the markets recently. recently. In bear periods, traders often sell the market when it hits a short-term high to exploit its downward bias. Indeed, historical testing shows SPY tends to drop sharply after hitting new five-day highs in bear markets (not shown). However, Table 5 shows SPY’s counter-rallies counter-rallies can be surprisingly strong if the market goes against you. 

14

Related reading “

Bull vs. Bear: The details matter

”

Active Trader, November 2002.

This comparison of bull- and bear-market characteristics provides concrete statistics upon which to base upside and downside trading strategies. “

Short-term stock market runs

”

Active Trader, July 2008.

A detailed look at how markets have tended to move following price runs of different lengths and sizes. Analyzing the bear

“

”

Active Trader, June 2008.

Measuring how the S&P 500 has responded to 20-percent drops in the past offers clues about what could be in store for the market. “

Losing your shorts

”

Active Trader, September 2002.

Short strategies are influenced by bear-market volatility and the short squeeze. “

Familiarity breeds profitability

”

Active Trader, September 2002.

This study analyzes price patterns to determine the odds that different kinds of price moves will occur. “

Know thy market

”

Active Trader, October 2001.

Regardless of what kind of trader you are or what approach you use, knowing the typical price behavior for the markets you trade is essential. Here’s how to do it. You can purchase and download past articles at http://store.activetradermag.com


TRADING Strategies

Combine and conquer: Testing a consensus approach Does technical analysis really work? Recent evidence shows combining different trading strategies is more profitable than following just one method.

BY CAMILLO LENTO

M

any traders argue

market when a buy consensus emerges

that you shouldn’t

among different trade signals, and you

rely on a single rule

sell the market when a sell consensus

to make trading

appears. Combining multiple signals

The mechanics of the CSA trading model

decisions. However, multiple trading

reduces the risk of selecting and relying

Two empirical tests were conducted to

rules can provide conflicting signals — a

on a single rule at any given time.

compare the profitability of the combined

significant, but common issue. For exam-

For example, you can use five trading

various trading rules.

signal approach to its individual trading

ple, on any given day, a 2-percent filter

rules — e.g., two MA crossovers, a per-

rules. Profitability was defined as gains

rule may signal a buying opportunity,

centage filter rule, moving average con-

that exceeded buy-and-hold after adjust-

while a 10/20-day moving average (MA)

vergence divergence (MACD), and

ing for transaction costs (bid-ask spreads

crossover rule may suggest the opposite.

Bollinger Bands — to develop a com-

and commissions).

One solution is to combine individual

bined signal that triggers a long signal

The first test used 12 trading rules

trading signals to form a consensus in

when three of the five rules are bullish.

from four categories: MA crossovers,

one direction. The following summary is

Or you can also use a stricter version that

price filters, trading range breakouts, and

based on a recent academic study that

requires four of the five signals to agree

Bollinger Band breakouts (see “Individual

describes a Combined Signal Approach

on a position.

trade rules” for more details).

(CSA) to technical analysis. The CSA

A combined approach offers an oppor-

The CSA strategy takes a long position

strategy weighs two or more trading rules

tunity to earn profits even when individ-

if “ x” or more of of the 12 trading rules rules

and calculates a combined signal that is

ual trading signals are unprofitable. The

point higher, and exits when the same

designed to be more effective than the

CSA strategy’s appeal lies in synthesizing

number of rules trigger a sell signal.

sum of its parts.

individual rules into a more powerful

When the system is out of the market, it

whole. It is likely a combined signal per-

earns 3-percent interest. We tested it

Strength in numbers

forms better because information related

using a consensus of seven and eight

With a combined approach you buy the

to future price moves is dispersed among

15

continued on p.

16


Trading Strategies continued

Individual trade rules

trade signals, representing more than 50 percent of the rules.

Testing the Dow and the Nasdaq Composite The first test used daily data of the Dow Jones Industrial Average (DJIA) and the Nasdaq Composite (COMP) indices from May 9, 1995 to Dec. 31, 2004. Table 1 (p. 17) shows the annual returns for all 12 trading rules and compares them to the buy-and-hold approach. The final three columns compare the average of all rules to the combined approach (seven and eight signals, respectively). The statistical significance of the profits is determined using a bootstrapping methodology. methodology. The combined

1. 50-day 50-day MA cross crossove overr rules rules:: a. Go long at the next day’s open if price closes above above its 50-day moving average. b. Exit at the next day’s day’s open if price closes below its 50-day moving average. 2. 200-da 200-day y MA cro crosso ssover ver rules rules:: a. Go long at the next day’s open if price closes above above its 200-day MA. b. Exit at the next day’s day’s open if price closes below its 200-day MA. 3. 5-day/150 5-day/150-day -day MA crossov crossover er rules: rules: a. Go long at the next day’s open if a five-day MA closes above its 150-day MA. b. Exit at the next day’s open if a five-day MA closes below its 150-day MA. 4. Bollinger Bollinger Bands Bands (20-day (20-day,, two standar standard d deviations deviations): ): a. Go long at the next day’s open if price closes above above the upper Bollinger Band. b. Exit at the next day’s open if price closes below below the lower Bollinger Band. 5. Bollinger Bollinger Bands: Bands: Same Same rules rules as no. 4, but but with paramete parameters rs of 20-day 20-day,, one standard deviation. 6. Bollinger Bollinger Bands: Bands: Same Same rules rules as no. 4, but but with paramete parameters rs of 30-day 30-day,, two standard deviations.

approach’s performance is shown with and without transaction costs. The combined signal approach earned more than the average of all 12 individual trading rules, especially in the Nasdaq Composite, which gained from

7. On Onee-pe perrcent cent filt filter er:: a. Go long at the next day’s open if price rises rises by 1 percent, without dropping below yesterday’s close. b. Exit at the next day’s day’s open if price declines 1 percent, without dropping below yesterday’s close. 8. Two-percent Two-percent filter: Same Same rules as no. 7 but use price price moves moves of 2 percent.

8.9 percent to 13.3 percent annually annu ally.. The Dow’s performance is most revealing: None of the individual trading rules

9. Five-per Five-percent cent filter: filter: Same Same rules rules as no. 7 but use price price moves moves of 5 percent. percent. 10. 50-day 50-day trading trading range range breakou breakout. t. a. Go long at the next day’s open if price climbs above above the most recent peak, defined as the highest high of t he previous 50 days. b. Exit at the next day’s day’s open if price drops below the most recent recent trough, defined as the lowest low of the previous 50 days.

generated profits, but the combined approach managed to gain ground. For instance, the individual rules lost 8.5 percent per year, on average, but the seven-signal CSA strategy posted a 2.7percent annual gain, including transaction costs (vs. 6.1 percent without costs). The eight-signal CSA strategy was also

11. 150-day trading trading range breakout: Same rules rules as no. 10, except use highest high and lowest low of prior 150 days. 12. 200-day trading trading range breakout: Same rules rules as no. 10, except use highest high and lowest low of prior 200 days.

profitable before transaction costs, and although it lost money after fees, its losscontinued on p.

16

17



TABLE 1: DOW AND NASDAQ, 1995 TO 2004

Annual returns (%) Dow Jones

MA crossover rule

Bollinger Bands rule

Filter rule

Tradi rading ng rang rangee breakout rule

Parameters

Parameters

Parameters

Parameters

1/50 1/200 5/150

Trading rules 2.3 Buy & hold 10.8 Profit -8.5 No transaction costs

Avg. vg. of Comb Combin ined ed sign signal al 12 rules approach

20/2

20/1

30/2

1%

2%

5%

50 days

15 1 50 days

200 days

CSA CS CSA (7/12) (8/12)

0.5 8.6 -8.2

2.6 10 -7.4

4.6 10.8 -6.2

4.3 10 10.8 -6.5

5.5 11.3 -5.8

-3 11.7 - 15

0.5 11.7 -11

0.3 11.7 -11

1.2 11 -9.6

0.5 10 -9.5

6.4 8.8 -2 - 2.4

2.1 10.6 -8.5

17 1 7.9 4.1 13.8

13.9 4.9 9

-12.3 6.4 -18.8

-10.8 6.4 -17.2

-8.2 6 -14.2

6 8.3 -2 - 2.2

-9.6 8.3 -18

-1.6 8.3 -9.9

15 6.4 8.7

18.4 4.9 13.5

18 4.1 14

5.6 6.2 -0.6

2.7 6.1

-3.4 1.5

NASDAQ

Trading rules 20.8 Buy & hold 6.4 Profit 14.4 No transaction costs

13.3* 8.9* 16.6* 15.1*

* returns that are significant at the 5% level of significance The combined signal approach was superior to trading all 12 rules individually, individually, especially on the Nasdaq Composite, which gained from 8.9 percent to 13.3 percent annually.

es were smaller than the individual trad-

nine trading rules — all of the first test’s

votes triggering a trade signal: two of

ing rules (-3.4 percent vs. -8.5 percent).

rules except those based on Bollinger

nine, three of nine, etc., up to six of nine

Bands. The test spanned 50 years of daily

rules. Testing a range of values provides

Longer test, fewer trade rules on the S&P 500

S&P 500 price data from Jan. 1, 1950 to

evidence for both a strict (6/9) and a

March 19, 2008. The approach was test-

loose (2/9) system. (There are not enough

The second test used a CSA model with

ed with different numbers of consensus

consensus signals to provide a robust test

TABLE 2: S&P 500, 1950 TO 2008

MA cr crossover rule Parameters Annual returns (%) No transaction costs

Trading rules Buy & hold Profit

1/50 1/200 5/150

Trading range breakout rule

Filter rule Parameters

Avg. of 12 rules

Combined signal approach

Parameters

1%

2%

5%

50 days

150 days

200 days

(2/9) (3/9) (4/9) (5/9) (6/9)

11 9.7 1.3*

11.3 9.5 1. 1.9*

1 10 0.8 9.7 1.1*

15 9.8 5.2*

7.3 9.8 -2.4

7.9 9.8 -1.8

7.7 9.7 -2

8.9 9.7 -0.7

8.9 9.5 -0.5

9.9 9.7 0.2

3.2*

1.8*

1.9*

1.8*

0.0*

7.7 9.7 -2

10 9.5 0.5*

10 9.7 0. 0 .3*

7.1 9.8 -2.6

0.9 9.8 -8.8

7.5 9.8 -2.2

7 9.7 -2.7

8.7 9.7 -0.9

8.8 9.5 -0.7

7.5 9.7 -2.1

1.6*

0.0*

0.1*

-0.2

-2 - 2.6

Transaction costs

Trading rules Buy & hold Profit

* returns that are significant at the 5% level of significance The combined strategy generated profits on the S&P 500, while the average trading rule lost 2.1 percent annually after trading costs. 17


KC

For more information about the following concepts, go to “Key concepts” on p. 63.

Related reading The profitability of technical trading rules: A combined signal approach by Camillo Lento and Nikola Gradojevic. Journal of Applied Business Research 23(1): 13–27. “

”

• Bootstrapping • Moving average convergence-divergence convergence-divergence (MACD) • Bollinger Bands

of a 7/9 system.) Table 2 is similar to Table 1 and compares the annual performance of each rule

A combined signal approach to technical analysis on the S&P 500 by Camillo Lento. Journal of Business and Economics Research, forthcoming. Working Working paper available at http://ssrn.com/author=97095 http://ssrn.com/author=970955. 5. “

”

Combined signal approach: further evidence from the Asian-Pacific equity markets by Camillo Lento. Applied Financial Economics Letters, forthcoming. “

”

to different versions of the combined approach. Again, the individual rules led to consistent losses in the S&P 500 as they did in the Dow. The average trading

22 of 24 tests with annualized profits as

tested in this study use daily prices, you

rule lost 2.1 percent annually after

high as 28.3 percent on the Jakarta

can always apply a combined framework

trading costs.

Composite index.

to rules that work with shorter or longer

However, the combined strategy gener-

The results are robust given that the

ated profits. Before transaction costs, all

combined approach was profitable in

versions of the CSA approach beat the

three different markets with various

market, and four of the five versions out-

parameters.

performed the individual rules’ 0.2-per-

data frequencies (tick, intraday, intraday, or weekly). The idea is simple — add multiple rules together so each one gets a directional vote, which avoids problems

cent average gain. The results are similar

Customizing the technique

caused by conflicting signals.

after adjusting for transaction costs,

One of the most important features of the

Additionally, Additionally, a combined signal appears

although a significant portion of the prof-

CSA approach is its flexibility f lexibility.. You can

to be more powerful than individual rules

its are eliminated. The 5/9 and 6/9 com-

use different trading rules to develop a

alone. This framework likely reduces the

bined techniques were the only systems

combined signal, change the number of

noise or imperfections of individual trad-

that lost money. This could be because its

rules that trigger it, and apply it to differ-

ing rules and synthesizes dispersed infor-

parameters are too strict, resulting in too

ent time intervals.

mation into a more potent signal.

few positions.

The examples used here look for inter-

The concept is supported by statistical-

Both tests show a combined approach

mediate- and longer-term trends. But you

ly significant profits in the Dow, Nasdaq

significantly improves upon the individ-

can also use shorter-term rules to develop

Composite, and S&P 500 in different

ual trade rules’ performance; it also

a day-trading strategy. In addition, this

time periods going back 50 years. By con-

removes problems associated with multi-

study used only long signals, but you

trast, most trade rules, taken individually,

ple conflicting signals. Further analysis of

can use a combined approach to also sell

were unprofitable during this period.

Asian-Pacific stock ma rket indices

short, instead of simply exiting the mar-

showed the CSA strategy was profitable in

ket. Finally, although the CSA strategies


For information on the author see p.

4 .

18

TRADING Strategies

Scalping: Playing the lean It’s not about the charts, says this trader. Scalping requires an understanding of the order book rather than support and resistance levels.

BY JOHN GRADY

I

f you’re a day trader who has

The scalper does not use a trailing

The following scalp strategy is based

always approached the market

stop. If he is fairly certain a move is over

on the concept of “leaning” on bids and

from a technical analysis perspec-

and he’s sitting in a six-tick winning

offers. It’s a setup scalpers look for every

tive, you might want to contem-

trade, he sees no reason to risk three

day — a setup that can lead to the infa-

plate spending a little less time looking at

ticks to capture another unlikely three

mous false breakout.

the charts and a little more time learning

ticks. He will take his six-tick profit,

how to read the order book.

move to the sidelines, and watch. If the

trading is that you must have access to a

move continues, he can always buy

market-depth trading platform — that is,

very infrequently. infrequently. They’re aware of major

again. If it doesn’t, he covered at the right

one that shows multiple levels of bids

support and resistance, but once they’ve

price.

and offers — to execute any scalping

Major players tend to look at charts

One important aspect of this type of

made a mental note of where these levels are, they stop looking at charts and start watching the bids and offers. Contrary to popular belief, scalpers generally are not looking to capture the bid-ask spread. Although scalpers might take one tick if that’s all they think they can get, they are typically shooting for anywhere from three to seven ticks, depending on current volatility. volatility. If the market is roaring in one direction, they will certainly take 15 or 20 ticks, rather than simply getting out just to take a profit. However, such moves are few and far between. In general, scalpers are looking to exit as soon as they feel the

Strategy snapshot Strategy: Leaning on the bid/offer. Strategy type: Intraday/scalping. Logic: If traders keep selling into a bid just below a major resistance level (based on the order book, not just a chart) and the price refuses to “go offer,” it’s usually a good indication of strength — a sign someone is going to try to run that level. The opposite would be true for an offer that refuses to go bid just above a major support level.

Entry: In the case of a long setup, attempt to enter just below or at the resistance level (no higher than a tick or two above). Reverse for a short setup.

Exit: Within three to seven ticks, in normal volatility conditions.

momentum has died. 19


strategy. If you’re using an execution plat-

FIGURE 1: INTRADAY T-NOTE

form that only shows the inside bid and offer, you are operating at a huge disadvantage and you will probably never make money as a day trader.

Trading the lean When entering with this strategy, strategy, you want to either go with the trend of the day or with a range breakout. For example, say the market has been fluctuating between 5 and 15 over the past hour and has slowly been narrowing toward 15. You are looking to buy the break through at 15 — as it occurs, not too long after the fact.

The longs tipped their hand before the break. No matter how many

The analysis follows the price action in the 10-year T-note futures on Aug. 25, 2008. After an early-session run-up after an economic report release, the market settled into a tighter range. Source: TradeStation

116-26.5 bid, 116-27 ask, it stopped and traded at those two prices for a while. There were 1,700 contracts offered at

down and were using it as resistance. In this situation, scalpers short at 26 or 27 are trying to limit their risk to two or

times sellers hit the

116-27.5 and it was obvious traders

three ticks. If it looks like 27.5 is going to

would be leaning on that price — which

go bid (i.e., become the current bid

26.5 bid, the price

represented resistance not because it was

price), they will try to cover there.

a line on a chart but because of the large

Scalpers who are looking to get long will

offer. In other words, shorts were hoping

also try to buy at 27.5 because they know

wouldn’t go offer. For example, on the morning of Monday, Aug. 25, 2008, the U.S. 10-year T-note futures (TYU08) made a large spike up after the release of economic data (Figure 1). The market stopped at 116-27.5 (a clear resistance level on any chart) and quickly sold off to 116-24. After a few minutes, price started to grind

the offer at 27.5 would keep the market

continued on p.

21

T-note futures prices Treasury futures prices indicate a percentage of “par” price, which for any Treasury bond or note is 100. T-bond prices consist of the “handle” (e.g., 100) and 32nds of 100. For example, 98-14 is a price that translates to 98- 14/32nds or $984.38 for a $1,000 T-bond. T-notes T-notes (the market referenced in this article) are priced in a similar fashion, except they can include one-half of a 32nd — for example, 98-14+ is 98-14.5/32nds, or 984.53 984.53 in decimal form. For simplicity, the prices in this article leave off the “/32” at the end.

back up again. When the market reached ACTIVE TRADER • January 2009 • www.activetradermag.com

20


the shorts are leaning on that offer.

be looking to make a trade once there is a

many contracts were sold into 26.5, the

This is an ideal situation because it

breakout through 27.5. A scalper is not

price wouldn’t go offer: sell 500, stays 26.5

represents a spot where new money is

looking to buy or sell the breakout. He’s

bid; sell 500 more, stays 26.5 bid; sell 300,

buying and scared money is exiting. That

looking to buy or sell before the breakout

stays 26.5 bid . If traders keep selling into

combination is what causes sharp price

or catch the breakout itself.

a bid and “they” keep buying and bidding

moves in one direction. In contrast, the average trader might

In this situation, the longs tipped their

that price, it’s usually an indication of

hand before the break. No matter how

continued on p.

2 2

Order depth The accompanying charts show snapshots of the 10-year T-note order book from Friday, Sept. 12, a day on which the market’s momentum was to the downside. The middle columns show price levels (116030 represents 116-3/32, and so on). The blue columns to the left show bids; the red columns to the right show offers. The market sold off sharply — 213 contracts traded at 116-01 and then heavy buying took place at 116- 01.5 (6,828 traded). This buying stopped the sell-off and the market retraced back to 03. However, the retrace- ment was short-lived and the market couldn’t stay bid at 02.5 (notice the 10,381 contracts traded at this price); no matter how many bids hit into 02.5, the market would not go up. Finally, the longs lost the battle. The 1,336 at 01.5 traded and the market went 01.5 offer (Figure B). Anyone leaning on that price was up the creek. The 01s got slammed and the market went straight to 115-31. FIGURE A: SEPT. 12, BEFORE THE BREAKOUT

FIGURE B: SEPT. 12, AFTER THE BREAKOUT

Source: X Trader

21



serious strength. When this type of action

attempt to keep the market down. You

often happens is someone with a lot of

takes place just below a major resistance

will lose that battle.

money buys everything in sight, which

level, it’s probably a sign someone is going to try to run that level. In this case, you want to buy at 26.5 or

was what happened on Aug. 25.

Flipping

There were 1,700 contracts offered at

This scenario also offers an opportunity

27.5 and 2,000 offered at 28 — and they

27 or catch the break at 27.5 or 28

for really big traders to hammer the

were all taken out at once. A huge trader

(maybe 28.5, tops). You don’t want to

shorts. It’s quite possible the offer at 27.5

just plowed through the market —

buy at 29, 30, or 31 because this is where

is not real — someone might be showing

bought 3,700 contracts and bid for 2,000

big money will exit. If someone was long

size with no intention of actually selling.

more at 28. No one even had a shot at

3,000 contracts going into that break, he is not looking for 10 ticks — he will try to cover on the immediate move up and will work offers between 29 and 31. Otherwise, if the market suddenly stops and he tries to dump 3,000 contracts, he could end up pushing the market against

27.5 or 28. Shorts scrambled for the door

The notion “Don't follow the herd” is nonsense. The saying

himself. Even if his selling doesn’t stop the market, you don’t want to buy when someone is dumping 3,000 contracts. You want to buy when everyone is buying — at 27.5. The notion “Don’t follow the herd” is nonsense. The saying should be “Follow

major players who have access to millions

not? You won’t. How will you know if someone is going to buy everything in sight? You won’t. All you can do is look (no matter how many contracts were sold

the herd and make

down) and go long somewhere between 26.5 and 28.

a sharp right just

No chasing

into that bid, the market just wouldn’t go

Although this was not one of those times,

before you reach

there are plenty of times you can catch the breakout as it’s happening. If you miss

the edge of the cliff.”

of dollars and who buy and sell thousands of contracts or shares — traders

How will you know if an offer is real or

should be “Follow

Following the herd is a great way to make money. The herd often includes

offer.

for the kind of action described at 26.5

the herd and make a sharp right just before you reach the edge of the cliff.”

and the market was instantly 29.5 bid, 30

the break and the market is suddenly trading 29.5 bid by 30 offer as it did this day, don’t go long. If you miss it, you

The trader who is long 3,000 contracts

miss it. You can be sure the guy who

who can actually move the market. You

at 26 might be the 1,700 offer at 27.5.

bought 3,700 contracts at 27.5 and 28

have to anticipate what the herd is going

When the market m arket gets heavily bid at 27,

already had offers at 29, 29.5, and 30

to do and then do it with them.

he will pull his 1,700 offer and bid 2,000

before he bought. His whole intention

at 27.5. This is called “flipping.” In one

was to cause a sharp upward spike and

herd if it means you’ll be the one holding

instant, the player has transformed the

cover as people panicked. Other longs

the bag. This is why you shouldn’t buy at

immediate market from a bearish to a

who were waiting for that rally were also

30 or 31. But you certainly don’t want to

bullish condition. Traders who are

covering at those prices. This is why you

be standing in front of a stampede; you

unaware of such tactics will be in for a

see many “false” breakouts (as if there is

don’t want to sell at 27.5 or 28 in this sit-

rude awakening.

such a thing), and why technical analysis

Of course, you don’t want to follow the

uation. If you know traders are leaning on a price, don’t join the offer in an 22

However, no flipping has to take place for the shorts to get hammered. What

kills many day traders. On this day, the market touched


Related reading

If traders are leaning on a price, don’t join the offer in an attempt to keep the market down. You’ll lose that

Harris Brumfield: Pit trader gets wired Active Trader , December 2003. “

”

Harris Brumfield, a pit trader turned screen trader turned technology entrepreneur, talks about pushing the volume envelope and the future of electronic trading. Mark Oryhon: DAX scalper Active Trader , December 2005. “

”

This active trader has developed the specialized skills necessary for integrating fast-moving market data on the fly.

battle.

Momentum scalper Active Trader , August 2006.

116-31 and then dropped all the way

A one-page Face of Trading profile of Richard Lopez, a 30-year-old trader who uses a scalping technique.

back to 116-25. If you’re long in a scenario like this, you want to cover when the big money is covering. If you’re long at 27 and the market spikes up, under no circumstance should you let it come all the way back to you. You might not want to have an offer working at 29 as the market is pushing up, but if you see it touch

“

”

Of molecules and markets Active Trader , June 2003. “

”

A one-page Face of Trading profile of Andrew Ackerman, a 34-year-old trader and former molecular biology research associate who uses a scalping technique. You can purchase and download past articles at http://store.activetradermag.com

31 and sell off back to 29.5, then you want to get out at 29. The technical trader who likes to buy support and sell resistance will short at

all the way back up through 30.

are, but because he knows how to read

Neither of these traders know what

the volume in the order book, he also has

27.5, and if his risk-control rules call for

happened because they don’t understand

a good feel for whether the level will hold

a five-tick stop-loss and a 10-tick profit

the mindset of scalpers.

or if a breakout will occur. Quite often,

target, he’ll exit the trade at 30 for a five-

he is the volume. The average trader can

tick loss and curse profusely while watch-

Trading beyond the chart

only buy or sell maybe five or 10 futures

ing the market fall right back to 25.

Knowing where the numbers are is not

contracts or a few hundred shares of

the problem for most day traders. It takes

stock. He cannot move markets.

The technical trader who likes to play breakouts will buy at 30 with the idea

a minute to look at a chart and make a

that resistance should become support, so

note of major price levels. The problem

ing, you have to think like the traders

when the market falls back to 27 (below

for most day traders is that they do not

who buy and sell thousands of contracts

the initial resistance of 27.5) he will exit

know how to read the order book. Their

and shares. And if you want to know

for a six- or seven-tick loss. He’s cursing

decision to buy or sell a certain price is

what they are thinking, you have to

twice as much as the short trader because

based upon nothing more than the fact

watch the bids and offers, not the

he doesn’t understand why the breakout

the price is a “support” or “resistance”

charts.

didn’t work — and he has to watch as

level on a chart.

the market touches 25 and then trades

A big scalper knows where the levels


If you want to make money day trad-


4 .

23

TRADING Strategies

Developing a trading system A look at at systemat systematic ic trading, trading, warts warts and all. all. BY ACTIVE TRADER STAFF

We hope to challenge

T

rading strategies are typically offered up in books and magazines as sets of crisp rules or programming code — neatly packaged, off-the-shelf commodities ready for consumption by the trading public. However, little light is shed on the process that went into arriving at those trade rules — even if the results of historical testing are discussed at length. The next 11 issues of Active Active Trader Trader will attempt to remedy this situation in a series of articles outlining our staff’s development and implementation of a mechanical trading system. The goal of the series is to fully illustrate the process of designing and trading a systematic strategy and, more importantly, importantly, show the realities of putting that strategy to work in the markets by risking money on it. We We will embark on this journey with as few preconceived notions as possible and we will fully disclose all the steps we take and the mistakes we make. We will develop the trading idea from scratch. And although we will make every effort to develop a profitable strategy that will perform well in the future — and we have more than a casual interest in this goal, since we will be risking our own money on it — we have no guarantee of success. (Also, we will be constrained by certain realities, including the fact that as full-time journalists we can trade only part-time, and that we have only a small amount of capital to risk.) We will present the articles to our readers so they can walk through the process with us and learn from our missteps — and hopefully, our successes. The following topics will be covered in the article series, but they do not represent everything it will touch upon. We don’t know what direction our research 24

notions regarding the ease and simplicity of systematic trading, and how different trading is from both historical testing and “paper trading.” will take us and we will report on the process as it develops; there are many other avenues this project might travel. 1. What market( market(s) s) we’ll we’ll trad trade, e, and why. 2. The type type of of approac approach h we’ll we’ll use, use, and the practicalities that will define it (amount of time available to execute trades, etc.). 3. Definin Definingg the initi initial al trade trade setup setup and determining its performance characteristics. 4. Develo Developing ping a test testing ing regi regimen. men. 5. Initi Initial al tes testi ting ng.. 6. Fleshin Fleshingg out out the the syste system: m: exit rules, money management, and risk control. 7. Rete Retest stin ing. g. 8. Interpr Interpreti eting ng the test test results. results. 9. Prepari Preparing ng to trade. trade. 10. Trading the system. system. 11. Comparison Comparison to to historical historical performance and to simultaneous paper trading. In chronicling the good and the bad, we hope the series will shed some light

on the difficulties of system design and systematic trading. More specifically, specifically, we hope to challenge popular notions regarding the ease and simplicity of trading in general — and systematic trading, specifically — and how different trading is from both historical testing and “paper trading.” As we have noted many times in Active Trader Trader , the gap between analysis and actual trading is a wide chasm indeed. As we start, it is apparent there are many basic questions that appear easy to answer but are quite complicated — and which will have important repercussions for the project as a whole. For example, to begin research and testing, we have to decide which instrument or instruments we want to trade. That decision will reflect certain assumptions and biases on our part, and will shape the subsequent research and trading. If we trade stocks, which stocks, and why? Why futures, or why forex? By opening one door we automatically close others. We have to make choices. This might not be the case if we had a large capital base to access, but we — like many individual traders — do not. Portfolio diversification is not a tool that will be at our disposal. Nor are we convinced a system must or should be traded on a portfolio basis (one of the more interesting concepts we will eventually address). Finally, Finally, we hope h ope to solicit feedback from our readers about the experiment as it unfolds, and will launch a blog on our Web Web site (www.activetradermag.com) (www.activetradermag.com) for that purpose.

Next month: Market selection and the general trading approach or type of strategy strategy we want to trade.


• January

2009

• ACTIVE TRADER

TRADING Strategies

Are options alternative ownership?

Maybe not Outright option positions shouldn’t be thought of as casual substitutes for stock or futures positions. They have advantages, but only in specific conditions.

BY KEITH SCHAP

Y

ou may have heard people talk about options as an alternative way to own a stock, gold, a Treasury note, or corn. The idea, these people say, is that where an ounce of December gold might cost $780 per troy ounce ($78,000 for one 100-troy-ounce contract), and require $5,500 initial margin, a December 800 call option might cost only $31 per troy ounce, or $3,100 for one contract. Buying a call option, then, seems to be an inexpensive way to own whatever it is you want to buy. Table 1 displays a sample of futures

prices, a stock price, the cash-equivalent value of one contract or round lot, the initial margin requirement, a relevant option strike price, the option quoted price, and the dollar price for one options contract. In every case, the call price is well less than the margin requirement, to say nothing of the cash-equivalent value. However, this is short sighted because it fails to take into account the true character of options and how they differ from futures or stocks. For one thing, when you buy a stock, gold, corn, or a Treasury note, you can hold your asset for a relatively long time

in anticipation of a price increase. This is not the case when you buy a call option. Time is the enemy of options buyers.

KC

For more information about the following subjects, go to “Key concepts” on p. 63.

• Option greeks (delta, gamma, theta, and vega) • Implied volatility • Out of the money • At the money

TABLE 1: COMPARING FUTURES, STOCK, AND OPTION PRICES AND VALUES

Futures price

Cash equivalent value

Initial margin

Option

Option price

Option price ($)

Gold

$780/oz

$78,000

$5,500

800 call

$31/oz

$3,100

Corn

433.50 ¢/bu.

$21,675

$2,025

440 call

37.50 ¢/bu.

$1,875

10-year T-note

111-24

$111,750

$2,970

112 call

1-51

$1,797

FedEx stock

$59.67

$5,967

60 call

$6.40

$640

The option prices may be less than the margin requirements, but this is only part of the picture when comparing options to their underlying instruments.

25


TABLE 2: TIME DECAY’S IMPACT ON THE 112 CALL

Futures price 111-24

Time

IV

90

7.8%

Initial rate 112 call 1.5%

Change (64ths)

1-38

80

1-32

4

70

1-26

6

60

1-18

8

50

1-11

7

40

1-02

9

30

0-56

10

20

0-45

11

10

0-29

16

Delta

Gamma

Theta

Vega

0.4832

0.2870

-0.6098 14.1125

0.4771

0.3516

-0.7495 11 11.5258

0.4641

0.4964

-1.0649

8.1388

Repricing a 112 call option at 10-day intervals, assuming no futures price, IV, or interest rate changes, isolates the time factor.

Further, the interaction of time decay, decay, implied volatility (IV) change, and underlying futures or stock price change affects options prices in ways futures or stock traders simply do not have to contend with.

FIGURE 1: TIME DECAY

Nailing down option pricing factors Accounting for the in teraction of these pricing factors in terms of the option greeks (delta, gamma, theta, and vega) can seem complex and daunting, but a few simple experiments can make it concrete and easy to understand. First, consider the effect time has on an option price. Assum e 10-year T-note futures (TY) are trading at 111-24, IV for the near-the-money 112 call is 7.8 percent, the interest rate is 1.5 percent, and there are 90 days to option expiration. Given all this, a 112 call option will cost 1-38 ($1,593.75). To isolate the time factor, reprice this option at 10-day intervals (down to 10 days until option expiration) assuming no futures price, IV, IV, or interest-rate in terest-rate changes. Table 2 displays the results of this experiment and Figure 1 graphs them.

The rate of decay accelerates, especially during the last three repricing periods.

Two things are obvious. The 112 call loses most of its initial value; the ending value is roughly 28 percent of the initial value. Also, the loss accelerates throughout the entire period and especially during the last three repricing periods. The table includes the greeks at 90, 60, and 30 days. For now, consider only the theta column. Theta values represent the option’s sensitivity to time; the larger the


theta value, the greater the effect of time decay. These numbers are negative to show the passage of time erodes option value. Notice the 60-day theta is roughly 0.14 greater than the 90-day theta. The 30-day theta is 0.315 greater than the 60-day theta. This squares with the observation of an accelerating loss of option value. continued on p.

27

26


TABLE 3: WHAT FUTURES PRICE BALANCES THE TIME DECAY?

Futures price

Time

112 call price

Implied vo volatility

Time

112 ca call pr price

111-24

90

1-38

7.8%

90

1-38

111-30

80

1-38

8.2%

80

1-38

112-05

70

1-38

8.8%

70

1-38

112-11

60

1-38

9.5%

60

1-38

112-18

50

1-38

10.4%

50

1-38

112-25

40

1-38

11.6%

40

1-38

113-01

30

1-38

13.4%

30

1-38

113-08

20

1-38

16.4%

20

1-38

113-15

10

1-38

23.2%

10

1-38

The futures price changes required to offset time decay are nearly the same, averaging 7/32.

Now let’s look at how much the futures price must rise at each 10-day interval to neutralize the effect of time decay and hold the 112 call price at 1-38. This experiment assumes no change in IV or the interest rate. Table 3 shows the results. The futures price changes are all nearly the same, averaging 7/32. Figure 2 graphs this information and again shows the futures price changes to be essentially linear. A third experiment considers how much the IV must increase at each 10day interval to neutralize the effect of time decay and hold the 112 call price at the initial 1-38 level. This experiment assumes a constant 111-24 futures price and no change in the interest rate. Table 4 and Figure 3 show the results of these repricings. Notice the IV at 10 days must be almost three times greater than the IV at 90 days to hold the 112 call price at 138. As the passage of time becomes increasingly erosive, it takes greater IV increases to achieve this balance. The vega column in Table 2 sheds light on this. Vega indicates how much a 27

TABLE 4: WHAT IMPLIED VOLATILITY BALANCES THE TIME DECAY?

The IV at 10 days must be almost three times greater than the IV at 90 days to hold the 112 call price at 1-38.

change in IV will change the option price. Notice the vega values decrease in contrast to the increasing theta values. Clearly, an option with a 14 vega is more sensitive to IV change than an option with an 8 vega. As a result, it will take a greater IV change to have the same effect on the option price, as apparent in Table 4 and Figure 3.

Toward the real options trading world In the real world, none of these things happens in isolation. The market conditions driving futures price changes also tend to result in IV shifts. All these options pricing factors — futures price, IV, and time decay — work together in

FIGURE 2: THE INTERACTION OF FUTURES PRICE CHANGE AND TIME

The findings in Table 3 reflect an essentially linear relationship.


FIGURE 3: THE INTERACTION OF TIME AND IMPLIED VOLATILITY CHANGE (IN TERMS OF PERCENT CHANGE)

shaping options prices. Two versions of another experiment illustrate this interaction. Assume similar initial market conditions as before, the one exception being 7.5 percent IV instead of 7.8 percent. Also, now assume the 10-year T-note futures price trends higher in regular 8/32 increments at each 10-day repricing moment. In the first version of the experiment, IV increases in quarter-percent (0.25 percent) increments; in the second version, it increases in half-percent (0.50 percent) increments. Table 5 displays the results of these As time passes, it takes increasingly larger IVs to maintain the call price.

continued on p.

29

TABLE 5: THE INTERACTION OF FUTURES PRICE, IV, AND TIME

Futures price

Time

IV

112 call price

111-24

90

7.50%

1-34

112-00

80

7.75%

1-39

112-08

70

8.00%

112-16

60

112-24

Change (64ths)

IV

112 call price

Change (64ths)

7.50%

1-34

5

8.00%

1-43

9

1-44

5

8.50%

1-50

7

8.25%

1-48

4

9.00%

1-57

7

50

8.50%

1-52

4

9.50%

1-62

5

113-00

40

8.75%

1-55

3

10.00%

2-02

4

113-08

30

9.00%

1-57

2

10.50%

2-04

2

113-16

20

9.25%

1-58

1

11.00%

2-04

0

113-24

10

9.50%

1-58

0

11.50%

2-00

-4

Change (64ths)

IV

115 call price

Change (64ths)

7.50%

0-34

The resulting call price changes yield relatively paltry returns. TABLE 6: OTM CALLS ARE POOR CHOICES FOR LONG-TERM TRADES

Futures price

Time

IV

115 call price

111-24

90

7.50%

0-34

112-00

80

7.75%

0-36

2

8.00%

0-38

4

112-08

70

8.00%

0-37

1

8.50%

0-42

4

112-16

60

8.25%

0-37

0

9.00%

0-45

3

112-24

50

8.50%

0-37

0

9.50%

0-46

1

113-00

40

8.75%

0-35

-2

10.00%

0-46

0

113-08

30

9.00%

0-32

-3

10.50%

0-43

-3

113-16

20

9.25%

0-26

-6

11.00%

0-37

-6

113-24

10

9.50%

0-17

-9

11.50%

0-24

-13

With 10 days to option expiration the call price has decreased enough to result in a net loss. ACTIVE TRADER • January 2009 • www.activetradermag.com

28


TABLE 7: BIG FUTURES PRICE AND IV CHANGES DURING A SHORT TIME MAKE FOR BIG OPTION RESULTS

Initial values

$ value

Ending values

111-24

113-24

90

80

Implied volatility

7.5%

8.5%

Interest rate

1.5%

1.5%

10-year T-note 112 call

1-34

10-year T-note futures Days to option expiration

Delta

0.4820

Gamma

0.2985

Theta

-0.5863

Vega

14.1108

Delta

0.2255

Gamma

0.2252

Theta

-0.4432

Vega

10.6552

$ result

ROI

1,531.25

2-51

2,796.875

1,265.625

82.65%

531.25

1-16

1,250.00

718.75

135.29%

0-34

10-year T-note 115 call

$ value

A shorter time frame minimizes the effect of time decay and maximizes the impact of futures price and IV increases.

two experiments. In both tables, the 112 call price increases, but the rate of the call price increase slows, and in the case of the larger IV increases, reverses direction. Notice the paltry returns resulting from these call price changes. In the case of the smaller IV increases, the gain is only 24/64 ($375). The case of the larger IV increases generates better results, but not by much. The move from the 1-34 initial call price to the 2-00 final call price results in a 30/64 gain ($468.75). The move from 1-34 to the 2-04 peak call price amounts to a 34/64 gain, or

$531.25. These gains pale in the face of the 2-00 ($2,000) futures price gain. Option trading specialists frequently recommend using out-of-the-money (OTM) options rather than at-the-money options such as the 112 call. Table 6 (p. 28 28)) repeats the experiment of Table 5, substituting the 115 call for the 112 call. In both cases, the call price increases slightly and then decreases enough to result in a net loss at the repricing 10 days to option expiration. Clearly, this is not a trade any rational trader would want to make.

A better deployment of options But the people who recommend using OTM options rank among the best professional traders. The long, drawn out sequences of Tables 5 and 6 must not be what they have in mind. The inescapable conclusion, it would seem, is that long options positions are best suited to situations where you anticipate both a significant futures price shift and a sharp IV increase — preferably in a relatively short time. Suppose you were to buy either the

TABLE 8: IN THE RIGHT CIRCUMSTANCES, CIRCUMSTANCES, OPTIONS CAN OUTPERFORM FUTURES

Contract cost ($)

Initial delta

No. of contracts

Position delta

Position cost ($)

Net gain ($)

10-year T-note

2,970.00

1

10

10

29,700.00

20,000.000

112 T-note call

1,531.25

0.4820

21

10.12

32,156.25

26,578.125

115 T-note call

531.25

0.2255

44

9.92

23,375.00

31,625.000

When the trades are set up to have roughly matching exposures, in terms of position deltas, the options improve considerably on the futures result.

29


112 or the 115 call option given the initial market conditions from Table 5. Now suppose the futures price rose two points to 113-24 and IV rose to 8.5 percent with 80 days to option expiration. Table 7 displays the details of these two trades. The shorter lifespan of these trades minimizes the effect of time decay, and the futures price and IV increases result in larger gains. The net result of the 112 call trade is $1,265.625, which amounts to an 82.65 percent return on investment (ROI, which is derived by dividing the dollar result by the initial dollar value: 1,265.625 / 1,531.25 = 0.8265). The net result of the 115 call trade is $718.75, which amounts to a 135.29 percent ROI. Still, these dollar results fall significantly short of the $2,000 futures gain. But look at the deltas of these two calls. The 0.4820 delta of the 112 call indicates this option has slightly less than half the upside exposure of a futures contract (by definition, the delta of a futures contract is one). The 0.2255 delta of the 115 call indicates this option has roughly 22.5 percent as much upside exposure as a futures contract. This means it requires a position long 21 of the 112 calls to have roughly the same upside exposure as a position long 10 T-note futures, given these market conditions (10 / 0.4820 = 20.75). Further, it requires a position long 44 of the 115 calls to have roughly the same upside exposure as 10 futures contracts. Table 8 shows the initial futures margin and option prices for one contract, the delta, the position cost (although margin isn’t really a cost), the position delta, and the net gain for positions long 10 T-note futures, 21 of the 112 calls, and 44 of the 115 calls.

Related reading “Optionality: Why options are better than insurance” Active Trader , November 2007.

Getting the most out of an options trade requires looking beyond the clichés and understanding how these tools really work. “Trading “Trading a trend: Adding o ptions to fu tures” Active Trader , March 2007.

Options can make it easier to take advantage of a longer-term trend, but you have to get the details right. “Keith Schap: Options Strategy Collection, Vol. 1” This collection contains articles from 2005 and 2006 written by Active Trader and Futures & Options Trader contributor Keith Schap, author of The Complete Guide to Spread Trading (McGraw-Hill, 2006). In these articles, he explores different options spreading techniques, seasonal trading strategies, and ways all types of traders can use volatility to their advantage. “Keith Schap: Futures Strategy Collection, Vol. 1”

This collection contains articles from 2005 and 2006 written by Active Trader and Futures & Options Trader contributor Keith Schap, author of The Complete Guide to Spread Trading (McGraw-Hill, 2006). These articles discuss a variety of futures (including single stock futures) spreading techniques, seasonal trading strategies, and using implied volatility in futures trading. You can purchase and download past articles at http://store.activetradermag.com

Once the trades are set up to have roughly matching exposures in terms of position deltas, the options improve considerably on the futures result. Notice also the lower cost of the 115 call; it’s even lower than the futures margin.

The bottom line Clearly, options should not be thought of as simple substitutes for futures or stock positions. The complex interaction of time decay and IV change, which does not play a role in futures or stock pricing, makes them ill-suited for this


simple substitution. Instead, outright call or put options should be the market tool of choice when traders anticipate very particular underlying price and IV developments within relatively short time horizons. This use of options allows you to capitalize on the inherent “optionality,” “optionality,” especially of an OTM call. Taking advantage of the way an OTM call value accelerates under these circumstances is the primary reason for trading options in the first place. For information on the author see p.

4 .

30

ADVANCED STRATEGIES

Volatility and swap spreads No market exists in a vacuum; each provides clues to where the others are going.

BY HOWARD L. SIMONS

F

or those of you who wish to become masters of counterintelligence, here is a surefire method of interrogation to separate financial professionals from pretenders: Start talking about swap spreads, the shape of the yield curve, and the term structure of fixed-income f ixed-income volatility. volatility. The pros will remain interested while the

poseurs will run out of the room screaming for mercy. This is a shame, for the intersection of the market indicators provides valuable insights into the direction of corporate bonds and, by extension, stocks. A swap spread is nothing more than the difference between the Treasury rate and the fixed-leg of a swap, which is the present

value of the yield curve. Here is a chain of causation commonly seen in the many financial crises of the past fifteen years:

FIGURE 1: THE YIELD CURVE LEADS VOLATILITY

1.To the extent increased credit stress induces a monetary response from the Federal Reserve, a flight-to-quality leading to both a steeper yield curve and to higher short-term interest rate volatility will ensue. 2.Higher short-term volatility expands swap spreads (the difference between Treasuries and LIBOR-based interest rate swaps). 3. As money money flees to the safety of the short-end of the yield curve, swap spreads expand faster there than at the long-end of the yield curve, thus leading to an inversion of swap spreads, which lead in turn to wider credit spreads for corporate bonds and their underperformance relative to Treasuries; and finally pressure on stocks.

Bond traders get nervous when yields plunge to what they think are unsustainably low levels. A steeper yield curve produced by Federal Reserve stimulus is viewed as a temporary situation; bond traders start to buy insurance against its unwinding, pushing volatility higher.

31

As they say at quitting time, that’s enough damage for one day. As these relationships go a long way toward narrating the demolition derby that was financial markets between January and September 2008, let’s take a look


FIGURE 2: THE TERM STRUCTURE OF INTEREST RATE VOLATILITY

at how they link together.

The yield curve The steeper yield curve as measured by the forward rate ratio between two and 10 years (FRR 2,10), the rate at which we can lock in borrowing for eight years starting two years from now, divided by the 10-year rate itself, leads the implied volatility on zero-coupon two-year Treasuries by thirteen weeks on average. An FRR 2,10 greater than 1.00 indicates a positively sloped yield curve; an FRR 2,10 less than 1.00 indicates an inverted yield curve. The relationship broke in June 2008, marked with a green arrow in Figure 1, when Federal Reserve Chairman Ben Bernanke indicated he was inclined toward raising short-term interest rates, but then it resumed in force. This relationship should not be surprising at all; bond traders get nervous when yields plunge to what they consider to be unsustainably low levels. A steeper yield curve produced by Federal Reserve stimulus is viewed, correctly, correctly, as a temporary situation, and bond traders start to buy insurance against its unwinding. This is why volatility rises in such a cycle.

During the 2000-2002 and 2007-2008 steepenings of the yield curve, the one- and especially the two-year note’s implied volatility shot higher, and by September they reached levels seen for Third World countries during currency crises.

FIGURE 3: TEN-YEAR NOTE YIELDS AND SWAP SPREADS

Term structure of volatility Thanks to the successive efforts of former Fed Chairman Alan Greenspan and Bernanke in procontinued on p.

33

Swap spreads spreads tend to rise in times of financial stress as investors move from the counterparty credit risk of the LIBOR world to the perceived safety of Treasuries. This relationship is likely to be distorted in the future as the bond market grapples with the astounding levels of federal debt created during the various bailouts of 2008.


32

Advanced Strategies continued

FIGURE 4: U.S. SWAP SWAP SPREADS SINCE JAN. JAN. 22, 2008

The more stressed the markets become, the more inverted the term of swap spreads. The shorter-dated swap spreads moved to levels well over their longer-dated longer-dated counterparties — a trend that exploded higher during the September 2008 financial crisis. (Each color band = 5 basis points.)

FIGURE 5: RISING SWAP SWAP SPREADS RAISE CORPORATE CORPORATE CREDIT SPREADS

viding us with two grand social experiments in rapid and violent steepenings and flattenings of the yield curve, we can map how the term structure of volatility changes during these events. Most bond traders regard the long end of the yield curve, 10- and 30-year bonds, as being more volatile because their tick movements and dollars per trade move more. It takes a little bit of training to remind ourselves the opposite is true; the shorter the maturity of an interest-rate instrument, the more volatile the change in its yield even though the dollar impact of that volatility will be less. During the 2000-2002 and 2007-2008 steepenings of the yield curve, the implied volatility term structure distorted in response to this verity (Figure 2, p. 32). The one- and especially the two-year note’s implied volatility shot higher, and by September reached levels seen for Third World countries during currency crises, not to cast aspersions on our beloved Federal Reserve. The volatility of the longer-dated bonds, the 10and 30-year issues, rose in both instances, but nowhere near as much.

Impact on swap spreads

Rising swap spreads reflect increased stress in the financial system, which should be reflected in credit spreads rising after swap spreads.

33

Swap spreads tend to rise in times of financial stress as investors move from the counterparty credit risk of the LIBOR world to the “safety” of Treasuries — safety being a relative term when the after-tax constant-dollar yield on Treasuries spent much of early 2008 in negative territory. We We can map ma p the paths of 10-year Treasuries and swap spreads over time (Figure 3, p. 32). The 1998 Long Term Capital Management crisis and the 2007 subprime crisis, both highlighted with a green vertical line, have a similar look. This relationship is likely to be


Related Related reading: Other Howard Howard Simons articles articles REITs REITs as macro indicators Active Trader , December 2008. Take a look at the sometimes surprising performance of REITs over the past several years. “

distorted in coming years as the bond market grapples with the astounding levels of federal debt created during the various bailouts of 2008.

Term structure of swap spreads Swap spreads also have a term structure. The lesson here is quite parallel to that seen for the volatility market, which makes sense given their similar impetuses from risk and sustainability considerations: The more stressed the markets become, the more inverted the term of swap spreads. If we map swap spreads across a range of tenors, or maturities, from the Jan. 22, 2008 panic low, low, we see how the shorterdated swap spreads moved to levels well over their longer-dated counterparties (Figure 4). This trend exploded higher during the September 2008 financial crisis. These inversions are hardly a sign of market health; they indicate banks are less willing to trade with each other than with the Treasury and demand a higher spread in recompense.

Impact on corporate bonds Finally, let’s see how swap spreads affect corporate bonds, both investment-grade and high-yield. If rising swap spreads reflect increased stress in the financial system, then we should expect the credit spreads to rise after swap spreads do. If we map the option-adjusted spreads for both investment-grade and high-yield corporate bonds led by the same 13 weeks we used before in discussing the relationship between volatility and the yield curve, we should see a tight relationship, and we do (Figure 5).

Following the money There you have it: Enough to bore the KGB into submission, but enough to know when to buy or avoid corporate bonds and, by extension, stocks. No capital market exists in a vacuum, and each one provides clues to where the others are going. For information on the author see p.

4 .

”

Deconstructing the commodity surge Active Trader , November 2008. Analysis of the factors driving the commodity boom offers offers insight regarding regarding the appropriate way to approach futures markets. “

”

The flight-to-quality trade Active Trader , October 2008. The rule has seemingly always been: Don’t ever be short bonds when stocks are getting clobbered. Is it still valid? “

”

Nothing could be finer than being a data miner Active Trader , September 2008. Analysis of large moves in three three markets has interesting implications implications for system traders. “

”

Putting the put-write right Active Trader , August 2008. Looking for a different edge in the stock market? See what comparing the Buy-Write (BXM) and Put-Write indices (PUT) reveals about the path of least resistance in the stock market. “

”

Crush spreads in a biofuel age Active Trader , July 2008. Take a look at how the biofuel industry is changing the soybean market crush spread. “

”

Energy stock movers and shakers Active Trader , June 2008. The surprising results results of analyzing the connection between oil and natural gas prices and the performance of energy stocks. “

”

TIPS, treasuries, and insurance Active Trader , May 2008. Do TIPS really have an advantage over regular T-notes T-notes and T-bonds? T-bonds? “

”

Gold: Sound and fury, signifying nothing Active Trader , April 2008. Gold has burst to new highs as the U.S. stock market and dollar have tanked, but don’t believe the easy explanations about the yellow metal’s role as an inflation barometer or hedge. “

”

Had enough of the dollar and stuff? Active Trader , March 2008. Analysis shows the relationship relationship between the dollar and commodity prices isn’t isn’t what most people think. “

”

Oil prices and global petroleum inventories Active Trader , February 2008. Is an oil shock — and even higher prices — a real possibility? “

”

Bonds and the first rule of trading Active Trader , January 2008. Where do we stand after a 25-year bond bull market? Get ready to adjust your T-bond and T-note strategies. “

”

Howard Simons: Advanced Currency Concepts, Vol. 1 A discounted collection that includes many of the articles listed here. “

”

You can purchase and download past articles at http://store.activetradermag.com


34

TRADING System Lab

Double-repo systems Double repenetration of a simple moving average sets up both long and short positions.

FIGURE 1: SAMPLE TRADE

BY VOLKER KNAPP

Market: Futures. System concept: In his book

Trading with DiNapoli Levels , Joe DiNapoli DiNapoli describes describes the double repo indicator, which represents the double repenetration of a specialized short-term moving average. The system was initially designed to trade from the short side. Here we will test both shortIn this ideal scenario, corn peaks in summer 2008, quickly creates a triple top, and side and long-side versions of the then turns south. system, the former on futures and Source: Wealth-Lab Wealth-Lab Developer Developer 5.1 the latter on stocks. The trade setup begins when a price thrust occurs. The definition of thrust is flexible; DiNapoli 1. Set Setup: up: does not provide a systematic definition in his book. In these a) Detect thrusting thrusting market market action when today’s high tests, it is defined as a move that exceeds the high 10 days ago is more than four times the 10-day ATR above the by a multiple of the average true range (ATR). This makes the high 10 days ago. parameter responsive to market volatility. volatility. In a proscribed amount of time of the up thrust, price must b) Within Within 10 days of this thrust, thrust, identify when price price close below a displaced simple moving average (SMA), which is closes below a three-day displaced SMA. a moving average shifted forward a certain number of bars; close back above the displaced SMA; then close a second time (the c) Wait for the closing closing price to cross cross back above the double repo) below the displaced SMA. DiNapoli uses a threethree-day displaced SMA. day simple moving average (SMA) displaced by three days; other moving average lengths could be tested. 2. Entr Entryy (futu (futurres): When es): When price closes below the The technique as DiNapoli originally described it also includthree-period displaced SMA a second time, enter short ed Fibonacci levels, profit objectives, and specific displaced tomorrow on a stop at today’s low. moving averages. The version tested here is a limited, objective representation of the pattern. Note: The entire setup and trade signal must occur within a 10-day span. Strategy rules: The setup rules are identical for the short (futures) and long 3. Exit: Cover Cover short at the market tomorrow when (stock) versions of the systems. The entry and exit rules differ the 13-day SMA crosses above the 26-day SMA. for each market. 35


FIGURE 2: EQUITY CURVE

KC

For more information about the following concept, go to “Key concepts” on p. 63.

Average true range • Average • Fibonacci levels • Simple moving average

The sample trade in Figure 1 illustrates a model case where the moving average crossovers happen relatively quickly. Money management: Allocate 3

percent of account equity per position. Starting equity: $1,000,000.

Deduct $2.5 commission and one tick of slippage per trade. Test data: The system was tested on

the Futures & Options Trader Standard Futures Portfolio, which contains the following 20 contracts: British pound (BP), soybean oil (BO), corn (C), crude oil (CL), cotton 2 (CT), E-Mini Nasdaq 100 (ND), E-Mini S&P 500 (ES), 10year T-Notes (TY), Euro currency (EC), gold (GC), Japanese yen (JY), coffee (KC), wheat (W), live cattle (LC), lean hogs (LH), natural gas (NG), sugar (SB), silver (SI), Swiss franc (SF), and T-Bonds (US).

The equity curve can be divided divided into three periods: two quick profit-earning periods separated by a long drawdown from 2001 to 2007. Source: Wealth-Lab Developer 5.1

FIGURE 3: PERCENT DRAWDOWN

Test period: October 1998 to

September 2008. Test results: The results were not

very encouraging — the system generated a profit of just less than 52 percent over the course of a decade. It signaled only 121 trades and had a winning percentage of just 45 percent. However, the low market exposure (around 7 percent) suggests risking a bit more than we did (3 percent equity continued on p.

An extended drawdown and low activity were big challenges for this system. Source: Wealth-Lab Developer 5.1

37


36

Trading System Lab

continued

STRATEGY SUMMARY: PROFITABILITY STRATEGY SUMMARY: TRADE STATISTICS

Profitability

Trade statistics

Net profit:

$591,842

No. trades:

121

Net profit:

51.98%

Win/loss:

45.45%

Profit factor:

1.62

Avg. profit:

0.76%

Payoff ratio:

1.76

Avg. hold time:

43.65

Recovery factor:

2.27

Avg. profit (winners):

5.24%

Exposure:

6.96%

Avg. hold time (winners):

51.76

Commission paid:

$598

Avg. loss (losers):

-2.97%

Drawdown

Avg. hold time (losers):

36.89

Max DD:

-17.52%

Max consec. win/loss:

5/4

Longest flat period:

1742 bars

per position) could have brought in more profit. On the bright side, the average profit per trade was a solid 0.76 percent, or about $4,300 — enough to not have to worry about trading costs. The equity curve (Figure 2) can be divided into three periods. The first one lasted until 2001 and was marked by increasing equity. In these three years, the system was able to earn nearly 30 percent. The next phase was an extremely prolonged drawdown (seven years), which bottomed out in March 2004 and finished near the end of 2007. The profits were essentially flat these years, moving back and forth. Finally, 2008 began another major profitable period — similar to the first in amplitude,

but much more volatile. On the whole, the system appeared to profit cyclically, gaining in short bursts after excruciating waits. Although Figure 3 shows the actual loss was never greater than 17.5 percent, it’s hardly possible to use a trading system that generates no signs of life for so long. The worst time for trading, emphasized in Figure 4, was 2001 to 2003 as commodities bottomed out before beginning a multiyear rise. However, the system did virtually nothing in 2005 and 2006. Figure 5 reveals out-of-balance net profit with lean hogs (LH) and corn (C) contributing the vast majority of profits.

PERIODIC RETURNS

Avg. return %

Sharpe ratio

Best return %

Worst Worst return %

% profitable periods

Monthly

0.39

0.03

13.18

-7.57

44.17

5

9

Quarterly

1.20

0.02

20.55

-5.00

47.50

5

4

Annually

4.22

0.09

21.20

-4.52

54.55

2

3

LEGEND Net profit — Profit at end of test period, less commission. Profit factor — Gross profit divided by gross loss. Payoff ratio — Average profit of

winning trades divided by average loss of losing trades. Recovery factor — Net profit divided by maximum drawdown. Exposure — The

area of the equity curve exposed to long or short positions, as opposed

Max consec. profitable

Max consec. unprofitable

(winners) — The average holding time ning trades. Avg. hold time (winners)

for winning trades. Avg. loss — The average loss for losing trades. Avg. hold time (losers) (losers) — The average holding time for losing trades. Max consec. win/loss — The maximum number of consecutive win-

ning and losing trades. Avg. return — The average percentage for the period. Sharpe ratio

to cash. Max. DD — Largest percentage decline in equity. Longest flat

— Average Average return divided by standard standard deviation of returns (annualized).

period — Longest period, in days, the system is between two equity

Best return — Best return for the period. Worst return — Worst

highs. No. trades — Number of trades generated by the system.

return for the period. Percentage profitable periods — The percent-

Win/loss — The percentage of trades that were profitable. Avg. profit profit

age of periods that were profitable. Max consec. profitable — The

— The average profit for all trades. Avg. hold time — The average

largest number of consecutive consecutive profitable periods. periods. Max consec. unprof-

holding period for all trades. Avg. win — The average profit for win-

itable — The largest number of consecutive unprofitable periods.

37


FIGURE 5: PROFIT CONTRIBUTION FIGURE 4: ANNUAL RETURNS

The system suffered three consecutive losing years as the commodities markets bottomed out. Source: Wealth-Lab Developer 5.1

Lean hogs and corn were responsible for the majority of profits. Source: Wealth-Lab Developer 5.1

Bottom line: This system was not optimized. We tested the

double-repo signal across a wide range of exit and parameter combinations — mixing channel breakouts, profit-taking stops, and time-based exits — and found some profitable results.

Nonetheless, trading this pattern from the short side, as taught by the author, although profitable, lacked consistency as well as an attractive rate of return. 

Test 2: Stocks In tests of the regular double repo pattern on various stock portfolios (not shown), the short-side system was always a loser — no wonder, given the multi-year stock market uptrend that lasted until late 2007. As a result, the following stock test reverses the signals — i.e., the setup remains the same, but the system now goes long instead of short. 1. Setup: FIGURE 6: SAMPLE TRADE-TEST 2 a) Detect thrusting market action when today’s high is more than four times the 10-day ATR above the high 10 days ago. b) Within 10 days of this thrust, identify when price closes below a three-day displaced SMA. c) Wait for the closing price to cross back above the three-day displaced SMA. 2. Entry (stocks): When (stocks): When price closes above the threeperiod displaced SMA a second time, enter long

tomorrow on a stop at today’s high. Note: The entire setup and trade signal must occur within a 10-day span. 3. Long ex exit: Sell at the market tomorrow when the continued on p.

39

This example of a failed double-repo pattern occurred during a prolonged uptrend and resulted in a nearly 100-percent profit. Source: Wealth-Lab Developer 5.1


38

Trading System Lab continued 13-day SMA crosses below the 26-day SMA.

FIGURE 7: EQUITY CURVE-TEST 2

Figure 6 shows a signal in Freeport Moran (FCX) that captured a long uptrend and generated a nearly 100-percent profit. Money management rules: Allocate 10 percent of account equity per position. Starting equity: $100,000. Deduct $2.5 commission and 0.10 percent slippage per trade. Test data: The system was tested on the S&P 500 stocks as well as the Active Trader Standard Stock Portfolio, which contains the following 17 stocks: Apple Inc. (AAPL), Boeing (BA), Citigroup (C), Caterpillar (CAT), Cisco Systems (CSCO), Disney (DIS), General Motors (GM), Hewlett Packard (HPQ), International Business Machines (IBM), continued on p.

The system produced a consistent equity curve throughout most of the test period. Source: Wealth-Lab Developer 5.1

40

STRATEGY SUMMARY: PROFITABILITY

STRATEGY SUMMARY: TRADE STATISTICS

Profitability

Trade statistics

Net profit:

$241,841

No. trades:

1,080

Net profit:

241.84%

Win/loss:

40.09%

Profit factor:

1.62

Avg. profit:

2.44%

Payoff ratio:

2.70

Avg. holding time (days)

27.20

Recovery factor:

4.63

Avg. profit (winners):

13.60%

Exposure:

60.86%

Avg. hold time (winners):

43.13

Commission paid:

$5,393

Avg. loss (losers):

-5.03%

Avg. hold time (losers):

16.53

Max consec. win/loss:

10/16

Drawdown

Max DD:

-14.32%

Longest flat period:

374 bars PERIODIC RETURNS

Avg. return %

Sharpe ratio

Best return %

Worst Worst return %

% profitable periods

Monthly

1.10

0.60

23.05

-6.00

57.50

6

6

Quarterly

3.33

0.62

26.78

-5.84

60.00

5

3

Annually

12.73

0.52

47.26

-5.21

81.82

5

1

39

Max consec. profitable

Max consec. unprofitable


FIGURE 8: PERCENT DRAWDOWN-TEST DRAWDOWN-TEST 2

Trading System Lab continued Intel (INTC), International Paper (IP), J.P. J.P. Morgan Chase (JPM), Coca Cola (KO), Microsoft (MSFT), Starbucks (SBUX), AT&T AT&T (T), and Wal-Mart (WMT). Data source: Yahoo.com. Period: October 1998 to September 2008. Test results: Tested on the small Active Trader portfolio, the system was spiritless and produced too few trades (around 50). To generate more trades, the system was next applied to all of the S&P 500 stocks. This resulted in 1,080 trades; 390 signals were rejected because of money management constraints. Most of the system’s drawdowns were short and shallow. The equity equity curve in Figure Figure 7 shows Source: Wealth-Lab Developer 5.1 steady gains for almost the entire test period, with low drawdowns from which the system recovered quickly (374 bars at FIGURE 9: ANNUAL RETURN-TEST 2 worst). The exit rule (after a SMA crossunder) resulted in some quintessential trend-following numbers, including the 40 percent winning percentage and the 2.70 payoff ratio. The manageable maximum drawdown of -14.3 percent (Figure 8) makes it possible to cope, and the strong 4.6 recovery factor leaves no doubt that that the strategy strategy can overcome future drawdowns. The portfolio's exposure is moderate at about 61 perThe system was profitable all but two years. cent, leaving room for an uncorrelated system to further reduce the risk of trading. Source: Wealth-Lab Developer 5.1 Overall, the system gained 13 percent on an annualized basis, slightly outperinfluenced by the fact that the test period was dominated mostly forming the buy-and-hold strategy overall (241.8 percent vs. by a strong bull trend.  231.6 percent net profit). The average profit (2.4 percent) was

enough to eliminate execution issues, since the system trades on stop orders. On an annual basis, as Figure 9 illustrates, only two years (2002 and 2008) were losers, and relatively small ones, at that (-5.2 percent and -3.7 percent, respectively).


4 .

Trading System Lab strategies are tested on a portfolio basis (unless otherwise noted) using Wealth-Lab Inc.’s testing platform. If you have a system you’d like to see tested, please send the trading and money-management rules to [email protected] .

Bottom line: The double repo, essentially a countertrend pattern that resembles a double top following an upward thrust, seems best traded from the long side in the stock market. Although it barely outperformed buy-and-hold, its risk was much lower. Coupled with a trend-following exit, it creates a strategy with a moderate risk level. However, the results are 40

Disclaimer: The Trading System Lab is intended for educational purposes only to provide a perspective on different market concepts. It is not meant to recommend or promote any trading system or approach. Traders are advised to do their own research and testing to determine the validity of a trading idea. Past performance does not guarantee future results; historical testing may not reflect a system’s behavior in real- time trading.


Trading setup

The Face of TRADING

Hardware: PC: Intel Quad core 2.4 GHz with 3 GB RAM, two 19-inch flat panel monitors.

Twists and turns

Laptop: Pentium 1.7 GHz with 1.23 GB RAM. Software: TradeStation, Interactive Brokers, Button Trader.

BY ACTIVE TRADER STAFF

Internet connection type: Redundant DSL and cable for back-up. Brokerage type: Interactive Brokers.

Name: Nolan Marchand Age: 40 Lives/works in: San Clemente, Calif.

N

olan Marchand first gained exposure to trading through a summer job during college as a runner on the options floor at the Pacific Stock Exchange in San Francisco. “This was back when it was still an open outcry outcry auction,” auction,” he says. says. “It was was very exciting, even though I didn’t know the first thing about options. The firm I worked for traded their own account and didn’t didn’t share many details about their methodology. The only thing I really learned was that if there is a flu bug going around on the trading floor, everybody gets it.” His next exposure came after college while working in Italy for two years as Europe switched over to its new common currency, the Euro. Marchand, a highschool math teacher at an American School in Rome, was paid in lira. Interested in how the changeover would impact his savings, he held some money in Euros and watched exchange rates and the fluctuations in his account. From there, he started reading books on trading, the markets, and technical analysis. However, Marchand’s career took several twists and turns. He returned to the U.S. and taught high-school math a few more years. Then he ventured into the mortgage brokerage business for four years, and he also rehabbed real estate in New Orleans. Marchand was living in New Orleans when Hurricane Katrina hit and devastated an old rooming house he had restored

and had been running as a youth hostel. He left New Orleans and resettled in Portland, Ore., where he began dabbling in currency trading. However, he mostly just bought and held the Euro, riding the major uptrend that occurred in recent years. After deciding to relocate to a better climate in California in early 2008, Marchand took the leap to full-time trading, with very little experience under his belt. Marchand had set aside enough money to pay his living expenses for a year, so he didn’t have to support himself through trading. He was attracted to the flexibility a trading lifestyle could offer. Initially, Marchand admits his trading was “schizophrenic” as he attempted to chase individual stocks based on chat room tips. However, through attending trading seminars and meeting a mentor, mentor, he has developed the very specific trading style he now implements. Trading Methodology: Marchand is a purely technical trader, scalping in EMini stock index futures. He puts on roughly three to five trades per day, which last approximately one to five minutes. He monitors 1-, 2-, 5-, 15- and 60minute and daily charts as he seeks to trade with the trend, entering on pullbacks. He trades both the long and short side. “I buy the first pullback from a base breakout, making sure there is support below and [no resistance above],” he says. “I hold my first contract for 10 ticks and my second contract gets trailed barby-bar on the one-minute chart. It may sound boring, but it works over and over again. I may only get three setups in a day. I may get 10. I may not get any. But


I’ve learned through expensive trial and error that if I deviate from my plan and start taking more aggressive trades, I lose money.” Marchand has also learned the importance of stepping away from trading intraday. “If I put on a trade and [it becomes] a losing trade, I set my kitchen timer and I don’t make another trade for 15 minutes,” he says. “That’s how I’ve gotten through my revenge-trade mentality.” Marchand has a set dollar amount for a daily goal. If he hits his goal and keeps on trading, but then gives back a third of profits, he’ll stop trading for the day. Or, if he is down $400 for the day, he’ll stop trading. Became profitable when: He developed a rule-based trading plan, wrote it down, and taped it to his monitor. “In between trades, I force myself to re-read these rules.” Most important lesson learned: “Don’t look for excitement. I look for boring, predictable patterns.” Best thing about trading: “If I hit my daily goal and it’s an hour into the morning, I can do other things.” Best trading books: Pristine course textbooks, Trading in the Zone by Mark Douglas. When not trading: Marchand gardens, spends time with his girlfriend, cooks, and swims in the ocean. He takes care of his health through yoga, meditation, and vitamins. 41

Q& A

Ken Grant on risk It’s no time to gamble, according to this top risk manager. Until things settle down, traders on both sides of the equity market are likely to get burned. BY MARK ETZKORN

FIGURE 1: AFTER THE 1987 CRASH

K

en Grant, founder of New York-based riskmanagement firm Risk Resources, concluded his Oct. 23 newsletter with an observation and a request: “The next several weeks are likely to resemble the last several weeks, which is to say that they will be murder to endure. I think that low or no risk is the way to go, but I guess you probably have surmised that already. But this time is different; this time I’m not asking, I’m begging you to be careful.” Volume dropped sharply after the 1987 market crash, and it took Although this might sound sound like shutting the corral door years for trading activity to return return to earlier levels. long after the bull has made its exit, Grant had begun sounding warnings about the high level of risk in the marFIGURE 2: CONTRACTING VOLUME kets 15 months earlier in 2007 — long before what many thought would be a market correction turned out to be a full-blown collapse. Grant is not just another talking head warning of the perils of the current market. Risk Resources, the 12employee firm he launched three years ago, specializes in hedge-fund risk management, and also consults for institutions, including the Chicago Mercantile Exchange, on risk matters. “We create and manage hedge funds’ reporting platforms,” he says. “I think we’re the only firm around that’s doing bona fide outsourcing of risk management.” Grant started the firm after a career in the risk-manage risk-manage-ment trenches that included stops at the Merc and French Volume Volum e has already dropped in the stock market in the aftermath bank Sociétié Générale, capped by several years with Steve of the September September-October -October flush-out. Cohen’s SAC Capital and Paul Tudor Jones’ Tudor Investments — firms at which he was in charge of designing and maintaining the risk infrastructure that dictated how already been pulled out of the market (see “Hedge-fund industry much traders could risk, the firms’ exposure, and how to maxishrinks by $210 billion in Q3,” p. 53), Grant pointed out there was much more liquidation on the horizon — and the market’s mize trader profitability. (See “Ken Grant: Confessions of a risk manager,” Active manager,” Active Trader Trader , December 2004.) high volatility and contracting volume promised to make the Grant was in no small part responsible for breaking the story of remaining redemptions more, not less, problematic than those the hedge-fund redemption situation as the market sell-off that had already occurred. (However, he believes the situation is reached a crescendo. Although billions of hedge-fund dollars had manageable.) 42


• January

2009

• ACTIVE TRADER

FIGURE 3: RECORD VIX

High volatility and low volume are part and parcel of a crash or flush-out. Volume contracted for more than a year after the 1987 stock market crash, and didn’t recover to pre-crash levels for nearly three years (Figure 1). A volume drop-off manifested itself immediately immediately after the initial Oct. 10, 2008 panic low (Figure 2), and volatility in the S&P 500 index in October and early November reached reached historic historic levels (see “Opening Trades” on p. 10 for details). I spoke with Grant in the hour leading up to the Federal Reserve’s interest-rate announcement on Oct. 29. He elaborated on his assessment of the financial crisis and the unique situation the markets were in as the year was winding down.

In August 2007 when the market really started to look pretty bad — multi-billiondollar quant strategies started having double digit monthly drawdowns, which were unheard of, and every week there was more bad news out of the credit space — I thought a couple of things would happen: Banks would write off many billions of dollars of credit losses and the Fed would flood the market with liquidity. Both those things came to pass. But I’m not claiming I had any huge foresight here — what I thought could happen was a small fraction of what actually transpired. For instance, I made a pretty aggressive negative call on equities on Dec. 31 in my The CBOE volatility index (VIX) came quarterly newsletter. I said there were two close to 90 as the market tumbled in October. The VIX’s median daily da ily close things that were going to push this market over the past five years is a little AT:: You pretty much laid it on the line AT down. First, the market couldn’t rally until below 15. in your last newsletter. the banks came clean and, second, the marSource: TradeStation TradeS tation KG: I’ve quite consistently recommended ket wanted cheaper money and would get people cut risk for about 15 months, and it — but this wouldn’t rally equities. I at every leg of the current situation I’ve thought that was a reasonably bold call, but what has happened in 2008 has been about five times as bad as tried to be a little more emphatic. Around the time of the Lehman Lehman bankruptcy bankruptcy I basically said, my worst-case scenario. “Look, we’re in uncharted territory — don’t trade. There’s no road It also was pretty clear to me in, say, December, there was a lot map here. Whatever Whatever skill set has gotten you to where you are is of “tape-painting” going on. When the markets rallied in not likely to serve you in good stead here. An environment environment in December it didn’t make any sense. People were obviously prowhich people can use investment-type analytical tools and insight tecting their books so they could get paid. to produce returns with consistency has utterly disappeared.” AT:: You mean money managers were buying to keep the AT After I put that report out, the VIX pounded its way toward toward 90 market propped up through the end of the year? (Figure 3). 3). The market still seemed completely broken to me and I wanted to be on record saying conditions were still deeply subKG: Unfortunately, I think something akin to that was indeed optimal. going on. Wall Street paid itself record bonuses in 2007, and they knew more about the extent of their problems than the outside “ The short side is probably even more world. In retrospect, it looks to me like they decided to take one last, massive payday, before the deluge. When I started telling people people to cut risk last August, at every treacherous than the long side.” point — and this includes through today ( Oct. 29) 29) — I was just trying to model the next six or eight weeks. And it just so hap AT:: What did you see 15 months ago that made you advise AT pened that at every point along the way things looked bad. When I reiterated this in February, I didn’t say we’d be on the verge of people to dial down their risk? KG: I had absolutely no idea this was going to become what it collapse in October, I was simply looking at the rest of the first has, but it was fairly clear to me there were very significant, conquarter. centrated risks the market couldn’t handle. I thought the risk preSomething else worth mentioning mentioning is that I went out of my way mium would continue to rise until we knew the extent of the to say the short side was probably even more treacherous than the continued on p. 44 credit problems in the economy. ACTIVE TRADER • January

2009

•


43

Q&A continued

long side. That’s what I believed then; that’s what I believe now. The things that have been most disastrous to hedge funds have been the government interventions. The really bad months earlier this year were March, when the market was tanking and the Bear Stearns [bailout] caused everyone to feel a bit better; and July, when crude was going up toward $150 barrel and banks were tanking. Then the government announced the groundwork for the Fannie-Freddie Fannie-Fr eddie [takeover] and energy started to reverse. If you look at charts of most of the major risk factors, you see a major inflection point around July 15 in equities, energy benchmarks, and credit benchmarks. It was an absolute turn-on-a-dime on the charts, which is not good for hedge-fund investments. investments. (The ( The July low is marked with an arrow in Figure 3.) 3.) I don’t know what’s going to happen right now, but I sure don’t think the upside justifies the downside, no matter what you do.

smart people tried to pick the bottom, and they’ve been burned and lied to. And we have to shake that out. The big examples are the financings that have occurred over the past six to nine months in the financial services sector — where, say, an investment fund comes in and lays money into a Merrill or a Lehman. The Mitsubishi UFJ episode was just a joke: They negotiated a 20-percent purchase [of Morgan Stanley] at $25 and a week and a half later the stock was at $7. And that weekend [Morgan Stanley CEO] John Mack was still saying the deal is going to go through under its normal terms. AT:: AT

Do you interpret a day like yesterday (Oct. 28, when the

S&P 500 tested the Oct. 10 low but rallied to close up more than 10 percent on the day ) as a good thing or evidence the

market is still broken?

One of my strongest opinions is the t he path toward a healthy capital market will not take the form of a v-bottom in the equity market. I was probably as happy as most people that the market rallied like it did, because at least it put some space between where I think the lows are and current levels. It could continue to go up — although I would guess it’s going to close down hard today because no matter what the Fed does [regarding interest rates], it’s going to be a sale for equities: If they don’t cut rates, the market will probably crash; if they cut 25 basis points, it will drop very deeply; if they cut 50 points, the market will want to signal to the Fed they want even cheaper money; and if they cut 75, everyone will say, “Look, they’re in full panic mode.” ( Note: The Fed cut rates 50 basis points and the S&P — after trading higher much of the day — closed down 1.9 percent.) percent. ) My primary scenario is there may be at least one more 10- to 20-percent down move before we can see where things are, and it would be driven by a combination of [rising] unemployment and a deeper consumer recession that’s not priced into the market. But until that happens, people will be sniffing around down near the October lows. If the S&P can rally 90 points yesterday, the next wave of selling isn’t going to crash through where I think the support is. I don’t root for the market to go up in an aggressive way right now because I don’t think there’s a framework for a sustained rally. Whenever I feel compelled to make a prognostication, it’s based on fund flows — not on a lot of fundamental analysis or financial analysis. When you look at approximately 400 portfolios every day, you start to get an idea of people’s decision factors. And in my opinion, everyone is waiting for a group consensus — that, say, corporate earnings in the U.S. can start to build from a worstcase scenario and that it’s a good time to funnel capital into [equiKG:

“

The market should recover, but it’s

going to take several quarters.

AT:: AT

”

What do you say to the argument that whenever things

seem to be at their worst, that’s when there’s the greatest opportunity?

I agree, but there are a couple of reasons it doesn’t dilute my current opinion in any way. First, the market is exceedingly treacherous — long and short. Do I think the market is cheap here? Yes. And I think a lot of the problems right now are driven by a combination of technicals and panic. But the point is this: It is still a market in deep disrepair. In terms of investment, it’s my very strong belief the market should recover, but it’s going to do so over several quarters. There’s a great deal to be said for waiting until the volatility comes out of the market. If you’re Warren Buffet, this is a good time to buy. If I had an unlimited amount of capital, sure, I’d buy a bunch of companies — and I’d probably buy a few condos in Florida, too. But since most people are trying to manage their returns, I think the [opportunities] will be no worse when the markets are functioning more normally and there’s more clarity. If you want to make some money as an investor in this market, [that’s going to happen] over a period of years. By contrast, I think it’s going to be very easy to get completely rolled over while the market is still broken, no matter what you do. One of the reasons we’re in this mess is because some very KG:

44


• January

2009

• ACTIVE TRADER

ties]. I certainly don’t see that right now. I don’t want to be a buzz-kill guy — I’m probably a little less pessimistic than most people I talk to. I think we can get out of this thing. The equity markets ought to be the first to recover recover,, and they can recover quickly — over the next year. But they’re not going to recover just because everyone is in desperation sell mode and then one day decides they’ve had enough. I just don’t think that’s plausible. AT:: AT

I know you’ve stated the market has priced in a certain

increase in unemployment, and the last number came in at 6.5 percent. How high do you expect the rate to go, and do

hedge fund space; their involvement, compared compared to previous crises, was entirely tangential. Although they’ve been buffeted buffeted very badly, badly, two things have kept hedge funds out of the spotlight. One, they report their numbers only monthly and, two, they tend to have — at most — “

The path toward a healthy capital

market will not take the form of a v-bottom in the equity market.

”

you think there’s a tipping point — a certain-sized increase increase in the next few months that would really knock the market for a loop?

The big fundamental overhang on the markets at the moment is unemployment and consumer spending declines, both of which I expect to accelerate over the next several months. Industries like technology are going to be hit with a double whammy, with their biggest source of clients — the financial services sector — taking spending down to zero, combined with a deep decrease in exports due to the sharp rise in the dollar. I don’t see how they can manage through this without deep job cuts, which in my opinion have barely begun. Remember, the global economy took a sharp negative turn after Labor Day, and this paradigm shift shift has not hit the labor markets yet. I suspect it will — dramatically — in the next couple of months, as corporate managers undertake 2009 planning cycles, recognize some dire realities, and start to reduce work forces in earnest. All of this translates into a deepening deepening consumer recession, recession, which should be the last big blow the equity markets take, but it will be a substantial one, as over 70 percent of U.S. GDP is driven by consumer spending. Bottom line: I see unemployment and declining consumer spending as the big catalysts for the last leg down in the markets, and I expect these events to transpire over the next two quarters. When we get there, the equity equity markets will be dirt cheap. cheap. But we ain’t there yet. KG:

AT:: AT

What do you see going on in terms of hedge-fund

redemptions? Have you seen more straightforward investor pullouts, or are funds getting crushed in their trading, too?

It’s a combination of the two. There’s been some alarmingly poor performance. But this was the first time in a long time a disaster wasn’t really [centered around] a hedge-fund trade. As this crisis has deepened there was virtually radio silence out of the KG:

ACTIVE TRADER • January

2009

•


quarterly liquidity (i.e., ( i.e., investors can withdraw funds only on a quarterly basis). basis). Risk reduction in the hedge-fund arena is just catching up. Let’s assume the whole world is trying to deleverage by 30 to 50 percent. Because of their lockups ( the minimum period investors must agree to leave their capital in a fund), fund ), hedge funds didn’t liquidate when, say, Lehman went bankrupt. My best guess is that around 25 to 30 percent of hedge-fund assets under management ( AUM ( AUM)) — several hundred billion dollars dollars — will go out the door by year end. AT:: And AT

you claim, all things considered, considered, the hedge-fund

redemption process is relatively stable?

I’m tracking this very carefully and it doesn’t appear the redemption process is any worse than I initially feared. [The money is] coming out in a relatively orderly fashion because, for instance, no counterparty risk has manifested itself. The fact that the hedge-fund industry has been reasonably proactive in recognizing the problems over the past year and a half and has reduced its risk has actually made things worse for people who are trying to reduce risk now. Non-invested hedge funds aren’t making markets, and they’re not the only ones. The sell side isn’t making making markets, either; volumes have dropped. The [market] is not particularly well equipped to accommodate the late liquidators. I just don’t see how it will end until into the first quarter, when everyone should know what their redemptions are and the dust should start to settle. Also, there’s a lot of uncertainty in the redemption redemption process. One One of the perennial problems in the hedge-fund space is that they raise capital very inefficiently — through fund of funds, capitalintro organizations, and similar channels. I’d estimate the average KG:

continued on p.

46

45

Q&A continued

dollar is intermediated at least a half-dozen times. That’s how the industry got to $2 trillion under management, but when the arrows are pointing the other way, there are a half-dozen points of redemption risk. It’s been a very uncertain process. The other big problem is many fund of funds have mismatched their funding. Some of them trotted across Europe and raised a lot of money. The Europeans wanted quarterly liquidity, so the fund of funds gave it to them. But on the other side, the fund-of-funds managers invested in hedge funds with two- or three-year lockups; they were giving quarterly liquidity when they didn’ didn’tt have the same liquidity on the other side. I know several fund of funds that have put in full redemptions to every one of their managers because because they had to. They’re hoping that when they find out what their redemptio redemptions ns are, they’re going to be able to cancel those redemptions or at least reduce them in size. My message to my hedge-fund and fund-of-funds fund-of-funds clients is that fourth-quarter performance performance is not anywhere near as important as franchise risk. I’m begging them to figure out what their Jan. 2 AUM is and to make sure they can adjust adjust to the point where on Jan. 2, their portfolio reflects reflects that AUM. AT:: AT

If they don’t, they’ll be massively over-leveraged, over-leveraged, right?

KG: Ye Yes, s,

but there’s a worse outcome than that, which which is that they may find themselves unable to meet even their year-end redemptions without causing enormous further damage to their returns. The late liquidators could lose significant amounts of money just raising cash to meet Dec. 31 31 redemption flows, flows, and if this happens, it’s likely their remaining investors will cry uncle themselves. This is why it’s so important to get in front of the liquidity management process. I think I can summarize by saying that hedge funds are seeing the same deleveraging by investors that every other pool has had, but it’s been orderly — much more orderly than, say, the liquidation of Lehman Brothers or the deleveraging of Citigroup. I find some irony in that since I’ve been listening for a decade to lectures from the [banks] about what we didn’t know about risk management. But it’s a painful process. Its biggest impacts are causing some very, very deep disruptions in the pricing patterns of the markets, but I think the industry can easily accommodate $500 to $600 billion of redemptions and rebuild from there. My last point is that when people do want to start taking risk again — when capital pools are seeking risk — a lot of money is going to come back to the hedge funds. 46

There are thousands of hedge funds that are down maybe 10 percent right now, but I’d say anyone down 10 percent is having one of the best alpha years they’ll ever have. But that’s not the message investors are taking right now. AT:: AT

Is sentiment worse or better than the beginning of the

month?

There’s a justifiable sense here in New York that something is gone for good. I think they’re probably overreacting, but you’re looking at the hedge-fund industry alone losing tens of thousands of jobs, and the financial services industry is going to lose many more. It’s people’s livelihoods and their investments. To use a very tired cliché, it’s very much a gut-check time. As I said, I’m probably a little more upbeat than most people, partly because it’s not the worst time to be selling risk-management services to multiple risk takers. But I believe one of the things that separates the real pros from the wannabes is the pros know bad markets — and good markets, for that matter — don’t last forever, and they plan accordingly. And the people who survive this are in a position to make a fortune. Right now people are very emotional; they’re not making particularly good decisions. And that’s what makes this the game it is: Sometimes it will break your heart. Also, somewhere somewhere down the road we’re we’re going to have to pay the piper if [the bailout plan] works. Because everyone knows, at least from a karma perspective, that it’s not good when the governments of this world have to throw trillions of dollars at a problem. That can’t be costless. We can’t use TARP ( the Troubled Asset Relief Plan)) and make a profit on it and have the Chinese continue to Plan fund our debt — it’s just not likely. KG:

AT:: AT

How might paying the piper manifest itself, other than

paying taxes through the nose?

Myriad ways: slow growth for years to come, less innovation, etc. All of this could make America a less lively and interesting place in which to live for a while. On the whole, though, I’m optimistic we will climb out of this mess, slowly, doggedly, but surely. The U.S. still has the best mechanism for monetizing innovation than any country in the history of the world. It has great people and vast natural resources. This year has been a real blow to us, but I think eventually, it will bring out the best in this country. Let’s just hope the Chinese don’t decide to dump our debt during the recovery process; that’s something I don’t even want to contemplate.  KG:


• January

2009

• ACTIVE TRADER

INSIDE the Market

Stagnant IPO, ETF listings reflect battered markets A lack of new companies going public speaks volumes about the current market condition, but a new study shows IPOs that survive a bad

In this section… Carbon trading on the rise

51

Gold update

51

Hedge funds take hit

53

Central banks slash rates

54

Managed money

55

Global numbers

56

environment may be stronger in the long run. BY CHRIS PETERS

I

n the biggest drought since mid2003, initial public offerings (IPOs) in the U.S. market have ground to a halt over the past few months. October and September were devoid of IPO activity — the latest signs of the stagnant market. But it’s not a U.S.-only phenomenon. A PricewaterhouseCoopers survey showed a 62-percent decrease in IPOs offered on European exchanges in the third quarter

of 2008 compared to the same period in 2007. Meanwhile, the Toronto Stock Exchange had no new IPOs in Q3 and only 10 from January through September, compared to 17 during the same period last year. Table 1 shows the number of IPOs in the U.S. market for each month back to 1998. Notice the sudden increase in total IPOs between 1998 and 1999 as the tech bubble inflated and the sudden drop-off

that extended through 2003. Following through on the momentum of 2004-2007, 2008 started out strong with 13 IPOs priced in January. But as the year progressed and the economic crisis began to accelerate, each new month returned a bleaker picture for companies thinking of going public.

Filings and withdrawals Figure 1 compares the number of compa-

TABLE 1: MONTHLY IPOS January February March April May June July August September October November December

1998 8 31 26 26 34 44 36 16 1 3 7 15

1999 9 29 21 33 48 52 61 39 40 60 57 37

2000 14 55 59 35 22 34 42 67 25 24 21 8

2001 3 6 8 3 8 15 7 5 0 7 9 12

2002 1 8 7 6 13 10 5 0 0 7 9 4

2003 0 3 1 0 1 1 8 6 6 10 15 18

2004 3 17 12 12 14 26 26 16 14 32 15 30

Total 247 486 406 83 70 69 217 The recent lack of IPO activity is reminiscent of the period following the dotcom crash.

2005 9 22 6 10 13 25 19 33 18 17 21 21

2006 11 25 16 18 14 21 14 8 16 22 28 30

2007 10 25 24 16 32 26 21 17 7 33 39 23

2008 13 6 3 4 7 3 4 3 0 0 n /a n /a

214

223

273

43

Source: Renaissance Capital’s IPOhome.com

47


FIGURE 1: IPO FILINGS AND WITHDRAWALS

nies filing IPOs with the Securities and Exchange Commission (SEC) in the past 24 months with the number of filed companies that are either postponing or withdrawing their IPOs. The former has declined significantly over the past year as the latter hit a recent high in October. Through October, 84 IPOs had been withdrawn or postponed, compared to only 17 during the same period last year. The IPO retreat is no surprise considering the market conditions of late. IPOs thrive in expanding markets and tend to pop up in the fastest-moving sectors. There were 573 technology IPOs in 1999 and 2000, more than the total number of IPOs from 2006 through October 2008 combined. Table 2 shows IPOs separated by industry. Even after the dotcom bubble burst, the tech industry remained one of the strongest in the field, producing a solid percentage of IPOs each year. Other resilient industries were the health care, energy, and (until 2008) financial industries. Overall, year to date through Nov. 4, TABLE 2: IPOS BY SECTOR Industry Business services Capital goods & services Communications Consumer Energy Financial Health care Materials SPAC Technology Transportation Utilities

1999 15 10 46 23 4 23 13 2 0 344 1 2

The number of IPO filings decreased over the past year and cancellations rose to a recent high in October. Source: Renaissance Capital’s IPOhome.com

new IPO pricings are down 80.1 percent compared to last year, while filings with the SEC have declined 53.7 percent. Although also down in number, nonU.S. IPOs have gained prominence, comprising 28 percent of all IPO proceeds in 2008. Last year non-U.S. IPOs comprised 19 percent of the total, a significant increase from 2002 and 2003 when they comprised only 6 percent.

2000 6 0 41 8 19 7 80 4 0 234 0 2

Only the strong survive An October report released by Greenwich, Conn.-based research and investment-management firm Renaissance Capital compared the current IPO drought to those in the past. Renaissance found only two other periods in recent history against which to measure today’s market: the three years following the burst of the dotcom bubble and the ecocontinued on p.

2001 5 3 0 7 10 12 24 1 0 19 2 0

2002 1 0 2 12 2 14 13 2 0 19 4 0

2003 8 1 6 6 1 17 8 3 0 15 4 0

2004 19 7 9 20 10 42 50 2 1 49 6 2

2005 6 5 12 20 20 31 34 9 22 32 20 3

2006 8 5 8 20 33 28 35 8 28 34 15 1

Total 483 401 83 69 69 217 214 223 Technology IPOs in the dotcom bubble era dwarfed the number of total IPOs launched since 2006.

4 9 4 9

2007 14 6 10 11 32 29 42 2 58 59 9 1

2008 2 3 0 1 7 3 4 2 12 5 2 2

273

43

Source: Renaissance Capital's IPOhome.com


48

Inside the Market continued

The extended

FIGURE 2: THREE-YEAR IPO PERFORMANCE

performance of IPOs released during the economy’s current downturn remains to be seen.

IPOs released during market downturns have tended to perform better in the long run because of the sound fundamentals required to make it through a turbulent market and the discounts at which the stocks are frequently offered. Source: Renaissance Capital and Jay Ritter, University of Florida

FIGURE 3: S&P VS. IPO INDEX

The cumulative monthly performance of the Renaissance IPO index compared to the S&P 500 shows the IPO index outperformed the S&P for the past three years. Source: Renaissance Capital's IPOhome.com and eSignal

released at a discount — sometimes up to 15 or 20 percent of what prices would normally be. The extended performance of IPOs released during the economy’s current downturn remains to be seen. The Renaissance IPO Index is a float-adjusted market capitalization-weighted index representing all IPOs capitalized with at least $50 million. They are added to the index at the close of their first day of trading and removed on the second anniversary of their listing. Figure 3 compares the index’s cumulative monthly moves to those of the S&P 500 from January 2003 through October 2008. The figure highlights the correlation between IPOs and the broader market. The IPO index took off relative to the S&P 500 in 2004 and from July 2004 until October 2007, when both indices peaked, the IPO index outperformed the S&P 70 percent of the time on a monthly basis. From the end of October 2007 through October 2008, however, the IPO index has lost 49 percent while the S&P 500 has dropped 37.5 percent.

ETF releases slow down in Q3 nomic recession of the 1970s. Figure 2 compares the yearly total of IPOs with the cumulative three-year average returns of the stocks. Although years of contraction yielded the fewest number of IPOs, those that were released during 49

these periods tended to fare better in the intermediate term than those released in other years. According to a Renaissance spokesperson, this is because investors tend to be more discriminating during these times and the IPOs are often

Through the third quarter, 173 new exchange-traded funds (ETFs) entered the U.S. market. And although Q3 had the lowest quarterly increase in two-and-ahalf years, 106 ETFs launched in Q2, helping to bring the year-to-date total just


FIGURE 4: ETF QUARTERLY INCEPTIONS

12 shy of last year. Figure 4 shows the ETF quarterly release totals going back to 2000. If the economic slowdown in the earlier part of the millennium is any indicator, the next few quarters will most likely produce far fewer ETFs than we’ve seen recently. Exchange-traded funds have come a long way since the S&P 500 Depository Receipts, or SPDRs (SPY) and Qs (QQQQ) launched 15 and 9 years ago, respectively. respectively. Since these instruments first revolutionized the way traders gained broad exposure to the S&P 500 and Nasdaq 100 indices, the ETF market has expanded dramatically d ramatically,, encompassing everything from individual equity sectors and international indices to short-selling portfolios and commodities. The number of ETFs has expanded from around 136 at the end of 2003 to more than 800 today. Not surprisingly, surprisingly, the most m ost recent releases from Q3 have had a rough time returning profits. One-month returns through Nov. Nov. 5 averaged -1.11 percent for all 26 ETFs with inception dates between July and September (Table 3). The fledgling ETF that has fared the best during the period has been the MacroShares MacroSh ares $100 Oil Down Do wn (DOY) ETF ET F, which tracks the inverse dollar price movement of crude oil. In 2008 nearly one-third of the ETFs released have been those offering exposure to specific commodity markets such as metals and energy. gy. When NYSE Euronext acquired the American Stock Exchange, they became the front-runner in ETF and exchangetraded note (ETN) listings, representing 61 percent of U.S. assets under management. (Exchange-traded notes are ETFlike securities that represent represent debt instruments, such as bonds.) The acquisition allowed the exchange to add the former AMEX’s portfolio of more tha n 400 ETFs and ETNs to its NYSE Arca trading platform and to expand its listings to more than 700 total.

The rate at which ETFs have entered the market has increased dramatically over the last few years. Source: Yahoo Finance

TABLE 3: PERFORMANCE OF Q3 RELEASES 1-month performance Name Symbol through Nov. 5 MacroShares $100 Oil Down DOY 14.31% SPDR S&P International Utilities IPU 9.06% SPDR S&P International Energy IPW 7.57% PowerShares Global Agriculture PAGG 6.29% ELEMENTS BG Large Cap ETN BVL 3.78% Market Vectors RVE Hard Assets Prod. H AP 3.40% SPDR S&P Intl. Tech. IPK 1.48% SPDR S&P Intl. Consumer Disc. IPD 1.24% iShares MSCI All Country Asia ex Jpn. AAXJ 0.98% PowerShares MENA Frontier Countries PMNA 0.53% SPDR S&P Intl. Consumer Staples IPS 0.31% ELEMENTS BG Total Market ETN BVT -0.43% SPDR S&P International Materials IRV -2.09% ELEMENTS BG Small Cap ETN BSC -2.20% Claymore/Raymond James SB-1 Equity RYJ -2.21% PowerShares Global Wind Energy PWND -2.45% SPDR S&P International HealthCare IRY -2.54% WisdomTree Middle East Dividend GULF -2.70% SPDR S&P International Industrial IP N -3.30% Claymore/Delta Global Shipping SE A -3.60% NETS Tokyo Stock Exchange REIT Index JRE -4.71% SPDR S&P International Financial IPF -5.31% SPDR S&P International Telecom IST -5.38% Market Vectors Gulf States M ES -9.09% Market Vectors Africa AF K -14.07% MacroShares $100 Oil Up UOY -17.77% Sector-based ETFs appear to be faring the best for young releases while regional ETFs have struggled. Source: Yahoo Finance and eSignal


50


Counting carbs

Carbon trading gains popularity Where there’s smoke, maybe there’s fire: Carbon debuts on the London Stock Exchange while volume on the climate exchanges grows. FIGURE 1: 2009 CFI CONTRACT PRICES

C

arbon began trading on the London Stock Exchange (LSE) as an exchange-traded commodity (ETC) on Oct. 30. The ETFS Carbon (CARB) ETC tracks the performance of the ICE Futures Europe exchange’s ECX EUA futures contract, which offers European investors direct exposure to the European Climate Exchange (ECX), emissions index. ECX volume reached a monthly record in October and experienced a 283-percent volume increase on the exchange over October 2007. The exchange’s stateside relative, the Chicago Climate Exchange (CCX), and its futures market, the Chicago Climate Futures Exchange (CCFE), have also seen increases in activity. The CCX Carbon Financial Instrument (CFI) futures and option contracts have increased in open interest from 1,689 contracts to a record high of 11,584 open contracts by the end of October.

CFI prices spiked dramatically earlier this year, and the number of contracts traded has increased substantially from last year.

As interest in the carbon trading market has increased, so has the price activity. As Figure 1 shows, CCX’s 2009 vintage CFI contract’s price action was fairly tame heading into 2008. However, from the beginning of the year to June 2008 CFI contract prices increased 289.5 percent, before falling over the next five months to

a new contract low. The exchange’s monthly report for October highlighted a 244-percent yearto-date increase in CFI contract volume over 2007. Combined with the CFI futures and options, 2008 has seen over 100 million metric tons of CO2 traded on the exchange.

Gold’s perplexing performance Gold’s ascension to all-time highs earlier this year was followed by a sharp drop — when stock really went into the gutter. Several factors are playing out in the market right now. BY ACTIVE TRADER STAFF

2

008 was a historic year for the gold market, which hit an alltime high in March as frontmonth futures topped $1,030/ounce and the soon-to-expire December 2008 futures (GCZ08) charged to $1,048 (Figure 1). But despite market chatter that $1,500 or even $2,000 gold would be next, the market abruptly reversed as the commod51

ity bubble burst and a dollar rally emerged as the stock market began to crumble in earnest. As a result, instead of pushing gold to the stratosphere, the October Massacre in stocks was accompanied by the yellow metal falling as low as $681 late in the month.

Dollar action Because gold is denominated in U.S. dol-

lars, the bear market in the greenback since 2002 was actually a bullish factor for the yellow metal. Figure 2 shows a monthly chart of continuous gold futures from January 2001 to November 2008. After nearly a decade of trading sideways from $275 to $400, gold bulls awoke in late 2002. The subsequent bull market pushed gold from $276 at the beginning of 2002 to $1,014


FIGURE 1 ALL-TIME HIGH

in March 2008. Meanwhile, crude oil rallied to an all-time high of $147/ barrel in July 2008, helping drive inflation concerns — a fundamental underpinning to the gold rally in recent years. This fall, crude oil fell sharply, sharply, removing inflation concerns, which took away some impetus to buy gold. Also, it was no coincidence that the U.S. dollar index plunged from 125.50 in January 2002 to 70.69 in March 2008. The buck’s recent upturn has acted as a major catalyst for some deflation in gold, crude oil, and other commodity markets this year.

Impact of high prices Gold’s rally above $1,000 understandably affected both supply and demand of the physical gold market. “We saw a sharp increase in scrap recycling,” says James Steel, senior vice president and metals analyst at HSBC. “A lot of gold that is held above ground is stored in jewelry or other forms that can be mobilized quickly, quickly, especially in the Middle East and India. $1,000 gold brought a lot of scrap to the market, which added greatly to supply. “$1,000 gold priced out a lot of jewelry purchases, so you had a reduction in demand. Jewelry is 70-75 percent of the physical gold demand,” he adds. According to World World Gold Council statistics, global jewelry consumption fell 24 percent in Q2 2008 vs. Q2 2007.

Gold topped out in March, and some of its sharpest losses since then occurred in October as the stock market collapsed. Source: TradeStation

FIGURE 2: GOLD FUTURES, 2001-2008

Financial system instability Other factors that dominated the gold trade in 2008 were the global credit crunch, financial system turmoil and sales, and bailouts and closures of a number of major players in the gold market. “There was a big push to be in cash and away from risk,” says Frank Cholly, senior market strategist at Lind-Waldock. “A lot of it had to do with strength in the U.S. dollar and the U.S. economy not

Gold climbed from $276 at the beginning of 2002 to $1,014 in March 2008. However, it has fallen sharply in the past six months. Source: eSignal

doing well, which eroded demand for all commodities including gold.” During September and October, hedge funds were forced to close out many posi-


tions because of customer withdrawals (redemptions), position squaring, and overall risk aversion. continued on p.

5 3 5 3

52


Trimming the hedge

Hedge-fund industry shrinks by $210 billion in Q3 The hedge-fund industry faces its worst year ever as poor performance and investor outflows peak.

T

he hedge-fund industry is poised to post its worst year ever according to Chicagobased Hedge Fund Research’s (HFR) third-quarter report. The hedge fund industry’s total capital shrank 11 percent from $1.93 trillion at the end of Q2 2008 to $1.72 trillion in Q3. The capital outflow of $210 billion in Q3 exceeded 2007’s entire capital inflow of $194 billion. “I think it’s a capitulation issue,” says Ken Heinz, President of HFR. “People indiscriminately want to be in cash at all costs and they don’t really care whether a fund’s doing well or doing poorly.” More than $31 billion of the loss was due to investor withdrawals, the single largest net capital withdrawal in the history of the industry. As of Nov. 7, indices

Gold continued from p.

Source: BarclayHedge

52

George Gero, vice president at RBC Capital Markets Global Futures, says gold futures open interest fell from 415,000 positions on Aug. 15 to 303,000 on Nov. 4. “That tells me there has been a major liquidation,” he says. “Hedge funds had to liquidate to meet margin calls in stocks. Nobody cared about inflation or deflation; they were being forced [to liquidate] by [their] prime brokers. Cash was needed by hedge funds, but a lot of gold traders, including Bear Stearns, Lehman Brothers, and AIG, are gone. In the short-term, you have lost a big part of the speculative audience.”

Coins and bars Amid the financia l market turmoil, physi-

53

tracking hedge-fund performance for the year were down by double digits. The Barclay Hedge Fund index was down 18.8 percent year-to-date through October, while HFR’s Fund Weighted Composite Index showed a 10.5-percent loss. If the trend continues through the end of the year, this could be the hedge fund industry’s industry’s first negative n egative yearly performance since 2002, when the average hedge fund declined by 1.45 percent. In September this year, hedge funds lost nearly 5.5 percent on average — the industry’s second-worst month. In August

TABLE 1: HEDGE FUND STRATEGY PERFORMANCE YTD through Sub indices Oct. Convertible Arbitrage Index -26.33% Distressed Securities Index -19.65% Emerging Markets Index -37.87% Equity Long Bias Index -24.48% Equity Long/Short Index -10.38% Equity Market Neutral Index -1.07% Equity Short Bias Index 37.85% European Equities Index -10.51% Event Driven Index -12.97% Fixed Income Arbitrage Index -18.27% Fund of Funds Index -16.76% Global Macro Index -3.09% Healthcare & Biotechnology Index -12.62% Merger Arbitrage Index -1.50% Multi Strategy Index -13.48% Pacific Rim Equities Index -15.86% Technology Index -10.15% Short-biased strategies are among the only to experience gains in 2008.

cal gold brokers saw the demand for gold coins and bars increase. “In October, we’ve seen a tremendous off-take in physical gold,” says Andrew Montano, director of precious metals at Scotia Mocatta in Toronto, a gold dealer. d ealer. “We’ve had real big demand in that area.” Montano found increased retail interest in owning physical gold during the equity meltdown in October. “It was a run away from feared currencies,” he says. “Gold is no government’s IOU. Gold is the ultimate reserve or store of wealth.

Monetary injections Some say inflation will ultimately reappear in the wake of the billions of dollars that have been injected into the global

banking system to relieve the credit bottleneck and the hefty cuts in official monetary policy rates by central banks around in the world. After all, an increase in money supply is generally thought to be inflationary. “Next year it may be a totally different picture because all this bailout money all over the world will inflate the currencies,” Gero says. “Inflation will rear its head and people will get back to looking at gold for fundamental reasons, not trading reasons.” However, gold bulls may need to bide their time. “Before we have inflation, we have to have a serious round of deflation,” Montano says. “Housing prices and commodity prices are still collapsing.” 


1998 hedge funds lost 8.7 percent, largely precipitated by the liquidation of the Long-Term Capital Management fund. Performance turned around that year, however, and funds overall still managed to end the year with a 2.6-percent gain. Although 1998 produced the worstperforming month, the actual drawdown lasted only about four months, whereas the current drawdown has already been much longer, stretching back nearly 11 months. Also, the circumstances are much different from a decade ago. “One interesting contrast is in 1998 the liquidation of a [single] fund precipitated poor performance and volatility at banks and financial institutions,” Heinz says. “[This time], the liquidation of banks and brokerage firms created a volatile, negative environment for hedgefund performance.” Table 1 shows the year-to-date performance for each of Barclay Hedge’s hedge-fund sub-indices. According to this data, mirrored in HFR’s performance indices, short-biased hedge funds have returned the best performance this year, returning profits in a sea of red, despite certain Securities and Exchange Commission (SEC) injunctions restricting some short sales. Funds focused on emerging markets appear to be hit the worst. As of Nov. 7, the Barclay Hedge Emerging Markets Index was down 37.76 percent year-todate through October. HFR’s emerging markets indices, which split the data into specific regions, show the worst performing to be those focused in Asia (except for Japan) and Russia/Eastern Europe. As the year he ads toward becoming the worst in history for the hedge fund industry, the outlook for the first few quarters of 2009 is none too bright as investors continue to jump ship. “The consolidation, which is ongoing, will continue into 2009,” Heinz says. For more information on implications of the hedge-fund contractions, see “Kent Grant on risk” on p. 42 42..

Central banks slash rates to prime markets FIGURE 1: U.S. DOLLAR INDEX As the world financial system sputters, finance ministers across the globe attempt to grease the wheels with lower interest rates.

I

n early October, the U.S. Federal Reserve, the European Central Bank (ECB), the Bank of England (BOE), and the Swiss, Canadian, and Swedish central banks jointly announced emergency 0.5-percent rate cuts. The Bank of Japan (BOJ) joined in support of the statement, but at the time did not participate in the coordinated rate cut. As the month wore on, the U.S. dollar, which had already begun to climb off the generational low it hit in March, accelerated to the upside (Figure 1). The U.S. dollar index (DXY) made some uncertain moves after hitting its all-time low in March, but by Oct. 28 had reached a nearly two-and-a-half-year high. On that day the U.S. Fed announced another 0.5percent rate cut, dropping the fed funds rate to 1 percent.

The U.S. dollar surged from August through October after a two-and-a-half-year slide. Source for for all bar charts: eSignal

FIGURE 2: YEN VOLATILITY

A worrisome yen It was the strength of another currency, currency, however, that had some people worried. Oct. 24 capped a surge in the Japanese yen (JPY) to a 13-year high against the dollar. This move prompted the Group of Seven (G7) finance ministers to release a statement saying “We are concerned about the recent excessive volatility in the exchange rate of the yen and its possible adverse implications for economic and financial stability.” Figure 2 shows the erratic behavior in the USD/JPY in October as well as the dollar’s drop to its lowest point vs. the yen since July 1995. Despite its already


October’s yen volatility prompted the G7 nations to release a statement of concern.

low rates, the BOJ decided to decrease its overnight lending rate from 0.5 to 0.3 percent on Oct. 31. On Nov. 6, the ECB decided to cut rates by another 0.5 percent, dropping its rate to 3.25 percent. The Bank of England also cut rates, as did the Swiss National Bank and the Danish central bank. Figure 3 displays the monthly average continued on p.

5 5 5 5

54

Inside the Market continued FIGURE 3: G7 INTEREST RATES

of interest rates among G7 countries back to the beginning of 2005. Rates peaked in the summer of 2007, but as the economic crisis grew, rates began to fall sharply, especially in September and October of this year.

U.S. dollar in four months through October following an AUD/USD peak at 0.9849 in July. The Reserve Bank of Australia lowered A worldwide issue rates by 0.75 percent Currency volatility has prompted many on Nov. 4 to 5.25. other countries to intervene as well. Mexico and Brazil Australia’s Central Bank began buying its have also had to step Interest rates among G7 nations have dropped significantly currency in an attempt to prop it up in in and support their in 2008 as nations across the globe attempt to inject cash into frozen markets. the wake of a decline to the lowest level currencies. Mexico’s vs. its U.S. counterpart in five-and-a-half Central Bank sold lion plan to provide liquidity by selling years. Figure 4 shows the Aussie dollar nearly $1 billion on Oct. 23 to support currency swaps. fell as much as 37 percent against the the peso, while Brazil unveiled a $50-bilMeanwhile, spot trading in the Icelandic krona halted in October after the nationalization of the island nation’s Barclay Trading Group’s September 2008 managed futures performance: top three banks. The Central Bank of Top 10 traders ranked ranked by September Septemb er 2008 return return managing managing Iceland quickly lowered rates 3.5 percent more than $10 million as of Sept. 30. to 12 percent. However, in a deal with Sept Septem embe berr 2008 2008 YTD YTD $ Unde Under r return (%) return (%) mgmt. the International Monetary Fund (IMF), Trading advisor the rate was raised by 6 percent to 18 99.87% 336.68% 30.3 1. Pere Trading Group percent for a $2 billion loan. 22.36% 74.84% 13.1 2. Edge Inv Mgmt (Gl Diversified) The IMF has also announced loan W. Henry & Co. (Gl. Analytics) 20.40% 47.56% 148.1 3. John W. deals with Hungary, the Ukraine, and 4. R.G. Niederhoffer (Negative Corr.) 17.24% 37.59% 852.7 16.95% 27.06% 131.2 5. Drury Capital (Diversified) Pakistan, while several other struggling 14.76% 38.30% 893.8 6. R.G. Niederhoffer (Divers.) emerging economies, such as Poland, 7. Amplitude Dynamic Trading Fund 14.48% 31.25% 800.0 Turkey, and Brazil, are expected to make 12.26% 26.06% 423.1 8. Hyman Beck (Global) pleas for assistance as well. 9. Aisling Analytics (Merchant Comm.) 10. R.G. Niederhoffer (TrendHedge)

12.10%

9.60%

2017.0

12.09%

26.83%

72.4

FIGURE 4: AUSSIE DOLLAR

Top 10 traders ranked by September 2008 return managing less than $10 million as of Sept. 30. 1.

Capital Alt. Invest. Mgmt

44.85%

123.99%

9.3

2.

District Capital Mgmt. (Divers.)

28.95%

4.24%

3.4

3. Ashley Capital Mgmt.

24.50%

8.76%

2.2

4. Attain Portfolio Advisors (Modified)

23.71%

41.37%

6.1

5.

Beechdale (Negative Gamma)

21.38%

30.08%

7.0

6.

T4T S.r.l. (System)

16.50%

87.76%

1.4

7.

Somers Brothers Capital (Divers)

15.01%

52.69%

3.6

8.

Parizek Capital (Futures)

14.68%

45.72%

1.1

9.

MarketEthos (ME Plus 3X)

14.48%

24.49%

6.7

13.78%

-4.90%

2.0

10. Valu-Trac Invest. Mgmt Strategic (2.5)

Based on estimates of the composite of all accounts or the fully funded subset method. Does not reflect the performance of any single account. PAST RESULTS ARE NOT NECESSARILY INDICATIVE OF FUTURE PERFORMANCE. Source: Barclay Hedge (www.barcl (www.barclayhedge.com) ayhedge.com)

55

Australian officials announced an aggressive plan to buy back the Australian dollar following a steep four-month slide.


Gross Domestic Product* Period

Release da date Ch Change

1-year change

Next release

AMERICAS

Argentina Brazil Canada

Release date Ch Change

1-year Next change release

AFRICA

Q2 Q2 Q2

9/17 9/10 8/29

20.0% 7.7% 2.5%

24.2% 1 2 . 9% 5.2%

12/18 12/9 12/1

EUROPE

France Germ any UK

Period

Q2 Q2 Q2

8/14 8/14 9/30

0.1% -0.1% 0.4%

3 . 5% 4.4% 4 . 4%

11/14 11/13 1 2/ 2 3

S. Africa Afric a

Q2

8/19

5.0%

16.2%

11/25

0.3% -2.3% -3.0% 0.9% -6.0%

2.7% 1 2/ 3 4 . 2% 11 / 1 4 16.3% 11 / 28 -0.6% N LT 11/19 2.1% N LT 11/21

ASIA A ND SO UTH PACIFIC

Australia Hong Kong India Japan Singapore

Q2 Q2 Q2 Q2 Q2

9/3 8/15 8/29 8/13 8/11

* Final estimates, at current prices, seasonally adjusted adjusted

Unemployment Period

Release date

Rate

1-year Next Change change release

Q2 Se p t . Oct.

9/22 1 0/ 2 3 11/7

8.0% 7.6% 6.2%

-0.4% 0 .0 % 0.1%

-0.5% -1.4% 0.4%

12/22 1 1 / 19 12 / 5

France Q2 9/4 Germ any S e p t . 1 0/ 3 0 UK June-Aug. 10/15

7.6% 7 .1 % 5.7%

0.0% -0.1% 0.5%

-0.8% - 1 .1 % 0 .4 %

12 / 4 1 1 / 27 11/12

Period

Release date

Rate

1-year Next Change change re release

AMERICAS

Argentina Brazil C anada EUROPE

ASIA A ND S OUTH PACIFIC

Australia Sept. 10 / 9 Hong Kong J ul uly-Sept. 10/20 Ja p a n S ep t . 1 0 / 31 Singapore Q3 10/31

4.3% 3.4% 4.0% 2 .2 %

0.2% 0.2% - 0 . 2% 0.0%

0.1% 1 1/ 1/6 -0.6% 11/18 0.0% 11/28 0.5% 10/31

Consumer Price Index (CPI) Period

Release da d ate Ch Change

1-year change

Next release

AMERICAS

Argentina Brazil C a n a da



AFRICA

Sept. Oct. S ep t .

10/10 11/7 10/24

0.5% 0.5% 0 .1 %

8.7% 6 . 4% 3.4%

11/11 12 / 5 11/21

EUROPE

France Germany UK

Period

S ep t . S ep t . Se p t .

10/14 1 0/ 1 5 10/14

-0.1% -0.1% 0. 0 .5%

3 .0 % 2.9% 5.2%

11/13 11/14 11/18

S. Africa Afric a

Sept.

10/29

0.2%

13.1%

11/26

1 .2 % 3.0% 0.7% 0. 0 .0% 0.0%

5 .0 % 4 .6 % 9.8% 2.1% 6.7%

1 / 28 1 1/ 2 0 11/28 11 1 1/28 1 1/ 2 4

ASIA A ND S OUTH PACIFIC

Australia H ong K ong India Japan Singapore

Q3 Sept. Sept. Sept. Sept.

10/22 10/23 10/31 1 0/ 3 1 10/23

Producer Price Index (PPI) Period

Release da d ate Ch Change

1-year change

Next release

AMERICAS

Argentina Brazil C a na d a



AFRICA

Sept. Oct. Se p t .

10/10 11/6 1 0 / 30

0.7% 1 . 4% -1.2%

11.6% 1 4 . 7% 8.0%

11/11 12/8 11/28

1 0 / 30 1 0 / 20 10/13

- 0 .4 % 0 . 3% -0 -0.3%

6.1% 8 .3 % 8.5%

1 1/ 2 8 11/20 11/10

EUROPE

France Germ any UK

Period

Se p t . Se p t . Se p t .

S. Africa Afric a

Sept.

10/30

-3.5%

16.0%

11/27

2 .0 % 1.7% -0.9% -0.4% -4.2%

5.6% 6 . 6% 11.0% 6 . 8% 9 . 9%

1/27 12 / 12 12 12/12 11 / 13 1 1 / 28

ASIA A ND SO UTH PACIFIC

Australia Q3 Hong Kong Q2 India Oct. Japan Se p t . Singapore Sept.

10/20 9 / 12 11/7 10/14 1 0/ 3 0

All data as of Nov. 7 LEGEND Change: Change from previous report release

NLT:


No later than

Rate:

Unemployment rate

56

Global MARKETPLACE FOREX (VS. U.S. DOLLAR)

Rank* Country

Currency

Current price vs. U.S. dollar

1-month ga gain/loss

3-month gain/loss

6-month gain/loss

52-week high

52-week low

Previous rank

1

Japanese yen

0.01007

5.98%

8.85%

5.94%

0.011

0.0087

1

2

Chinese yuan

0.14683

0.36%

0.51%

2.46%

0.14683

0.1339

4

3

Hong Kong dollar

0.12903

0.24%

0.69%

0.57%

0.12903

0.1279

3

4

Indian rupee

0.02105

-1.36%

-11.11%

-14.57%

0.03842

0.01843

13

5

Singapore dollar

0.67779

-1.72%

-6.72%

-7.77%

0.7434

0.6594

7

6

Taiwanese dollar

0.03049

-1.96%

-6.44%

-7.10%

0.03335

0.02974

6

7

Thai baht

0.02887

-2.07%

-3.70%

-9.19%

0.03396

0. 0.02775

2

8

Russian ruble

0.03726

-2.99%

-12.29%

-11.50%

0.04334

0.03652

10

9

Swiss franc

0.85814

-3.10%

-9.76%

-9.55%

1.0375

0.8471

8

10

Brazilian real

0.4731

-4.34%

-25.66%

-21.89%

0.6414

0.394

17

11

Euro

1.29369

-6.06%

-16.62%

-16.36%

1.6038

1.2329

12

12

Canadian dollar

0.8652

-6.37%

-9.98%

-12.01%

1.1038

0.768

9

13

Swedish krona

0.12979

-8.51%

-20.69%

-21.60%

0.1718

0.1235

14

14

New Zealand dollar

0.60431

-8.73%

-16.76%

-22.86%

0.8214

0.5349

11

15

British pound

1.59487

-9.98%

-18.53%

-19.15%

2.1161

1.5276

5

16

Australian dollar

0.69334

-10.46%

-24.78%

-26.29%

0.9849

0.6005

16

17

South African rand

0.10332

-12.84%

-24.47%

-21.83%

0.1555

0.0841

15

As of Nov. Nov. 6 *based on one-month gain/loss gain/loss

ACCOUNT BALANCE Rank 1 2 3 4 5 6 7 8 9 10 11 12

57

Country Singapore Switzerland Hong Kong China Taiwan Sweden Germany Netherlands Russia Japan Canada B Brrazil

2007 39.157 70.797 28.038 371.833 32.979 38.797 252.501 52.522 76.163 210.967 12.726 1.712

Ratio* 24.269 16.577 13.534 11 1 1.336 8.603 8.53 7.603 6.758 5.906 4. 4.815 0.886 0.13

2006 29.765 57.192 22.936 249.866 26.3 33.297 177.664 55.874 94.34 170.437 17.838 13.621

2008+ 37.099 45.731 26.191 39 3 99.325 33.09 33.041 279.017 51.107 115.286 19 194.269 14.803 -29.215

Rank Country 13 Mexico 14 France 15 In I ndia 16 UK 17 U.S. 18 Australia 19 South Africa 20 Spain

2007 -5.813 -30.588 -15.494 -105.224 -731.214 -56.342 -20.55 .557 -145.141

Ratio* -0.568 -1.179 -1 - 1.408 -3.752 -5.296 -6.198 -7.262 -10.079

2006 -2.231 -15.439 -9.8 -82.975 -788.115 -40.362 -16.602 - 11 110.14

+ 2008 -15.882 -83.488 -34.58 -101.454 -664.125 -52.555 -23.908 -169.209

Totals in billions of U.S. dollars *Account balance in percent of GDP +Estimate Source: International Monetary Fund, World Economic Outlook Database, October 2008


• January

2009 •

ACTIVE TRADER

NON-U.S.-DOLLAR FOREX CROSS RATES Rank

Currency pair

1 Franc / Pound 2 Real / Aussie $ 3 Real / Pound 4 Euro / Yen 5 Canada $ / Pound 6 Franc / Canada $ 7 Franc / Euro 8 Real / Canada $ 9 Real / Euro 10 Canada $ / Euro 11 Aussie $ / Pound 12 Pound / Euro 13 Aussie $ / Canada $ 14 Aussie $ / Euro 15 Aussie $ / Franc 16 Franc / Yen 17 Real / Yen 18 Canada $ / Yen 19 Pound / Yen Aussie $ / Yen 20

Symbol

Nov. 6

1-month gain/loss

3-month ga gain/loss

6-month gain/loss

52-week high

52-week low Previous

CHF/GBP BRL/AUD BRL/GBP EUR/JPY CAD/GBP CHF/CAD CHF/EUR BRL/CAD BRL/EUR CAD/EUR AUD/GBP GBP/EUR AU AUD/CAD AUD/EUR AUD/CHF CHF/JPY BRL/JPY CAD/JPY GBP/JPY AUD/JPY

0.53824 0.68278 0.29677 1.86711 0.54274 0.99239 0.66342 0.54711 0.36575 0.66889 0.43493 1.23315 0.80181 0.53633 0.80818 85.21795 46.97731 85.91263 158.388 68.83476

7.63% 6.76% 6.25% 4.87% 4.00% 3.45% 3.13% 2.13% 1.78% -0.38% -0.54% -4.21% -4.40% -4.67% -7.65% -8.65% -9.83% -11.74% -15.10% -15.59%

10.79% -1.13% -8.72% 10.90% 10.54% 0.27% 8.24% -17.40% -10.84% 7.97% -7.64% -2.28% -16.42% -9.73% -16.64% -17.11% -31.73% -17.32% -25.17% -30.93%

11.90% 6.00% -3.36% 13.50% 8.85% 2.81% 8.16% -11.21% -6.61% 5.19% -8.81% -3.33% -16.22% -11.83% -18.52% -14.64% -26.30% -16.98% -23.70% -30.45%

0.5677 0.7391 0.339 169.958 0.5427 1.1152 0.6992 0.6719 0.4197 0.7476 0.4895 1.4418 0.9833 0.6411 1.0629 105.071 69.3981 124.527 239.811 107.167

0.4147 0.6171 0.2441 113.614 0.482 0.8044 0.5969 0.4726 0.3124 0.6164 0.3786 1.2181 0.7568 0.4725 0.712 78.73 40.999 72.8508 139.276 55.1876

5 15 19 14 6 4 2 18 17 3 13 1 10 7 12 9 20 11 8 16

GLOBAL STOCK INDICES Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Country

Nov. 6

1-month gain/loss

3-month g ai ain/loss

6-mo -month ga gain/loss

52-wee week high

20,1 0,125.2 25.27 7 9,555.41 4,272.40 16,715.00 5,924.90 3,387.25 4,106.50 19,650.86 4,813.57 36,362.00 904.88 8,899.14 1,819.20 9,734.22 13,790.04

-4.2 -4.27 7% -6. -6.60% -6.90% -7.01% -8.26% -8.75% -9.64% -9.65% -10.64% -13.63% -14.38% -15.03% -16.10% -17.52% -17.93%

-25 -25.31 .31% -28.97% -22.12% -24.60% -17.82% -23.85% -18.17% -28.13% -26.64% -36.81% -29.81% -32.86% -36.98% -35.42% -37.61%

-36. -36.9 97% -33 -33.71% -31.26% -35.85% -21.46% -32.80% -28.93% -37.06% -31.40% -48.20% -36.20% -36.90% -44.00% -43.97% -47.49%

33,2 3,232.8 32.89 9 15,154.80 6,610.90 30 30,403.00 8,918.80 5,795.22 6,741.40 32 32,292.90 8,117.79 73,920.00 1,523.57 16,107.70 3,632.76 21,206.80 29,962.90

Index

Sout South h Afri frica FTS FTSE/ E/JS JSE E All Shar Share e Canada S&P S&P/TSX composite UK FTSE 100 Italy MIBTel Switzerland Swiss Market France CAC 40 Australia All ordinaries Mexico IP C Germany Xetra Dax Brazil Bovespa U.S. S&P 500 Japan Nikkei 225 Singapore Straits Times India BSE 30 Hong Kong Hang Seng

52-wee week low Previous

18,3 8,363.6 63.69 9 8,53 ,537.34 3,665.20 14,521.00 5,265.90 2,959.29 3,693.90 16,480.00 4,014.60 29,435.00 839.80 6 ,9 ,994.90 1,473.77 7, 7,697.39 10 10,676.30

6 15 5 7 2 3 1 11 4 12 13 10 9 14 8

GLOBAL SHORT-TERM SHORT-TERM INTEREST RATES RATES Country U.S. Japan Eurozone UK Canada Switzerland Australia New Zealand Brazil Korea Taiwan India South Africa

Interest rate Fed funds rate Overnight call rate Refi rate Repo rate Overnight funding rate 3-month Swiss Libor Cash rate Cash rate Selic rate Overnight call rate Discount rate Repo rate Repurchase rate

Rate 1 0.3 3.25 3 2.25 2 5.25 6.5 13.75 4 3 7.5 12

Last change 0.5 (Oct. 08) 0.2 (Oct. 08) 0.5 (Nov. 08) 1.5 (Nov. 08) 0.25 (Oct. 08) 0.5 (Nov. 08) 0.75 (Nov. 08) 0.5 (Oct. 08) 0.75 (Sept. 08) 0.25 (Nov. 08) 0.5 (Oct. 08) 0.5 (Nov. 08) 0.5 (June 08)

May 08 2 0.5 4 5 3 2.75 7.25 8.25 11.75 5 3.5 7.75 11.5

November 07 4.5 0.5 4 5.75 4.5 2.75 6.75 8.25 11.25 5 3.25 7.75 10.5

GLOBAL BOND RATES RATES Rank 1 2 3 4 5

Country UK Germany Australia Japan U.S.

Rate Short sterling BU B UND 10-year bonds Government Bond 10-year T-note

Nov. 6

96.325 117.52 94.85 137.84 115.43

1-month 1.86% 0.30% -0.03% -0.76% -2.15%

3-month 2.26% 4.14% 0.92% 0.43% 0.83%

6-month 1.71% 2.89% 1.30% 1.06% 0.51%

High 96.41 118.5 95.18 141.90 120.03

Low 93.60 109.65 93.18 132.09 110.83

Previous 5 1 4 3 2

All data as of Nov. 6 ACTIVE TRADER • January

2009

•


58

ETF Snapshot Date: Nov. 6 The following table summarizes the trading activity in the most actively traded exchange-traded funds. The information does NOT constitute trade signals. It is intended only to provide a brief synopsis of each market’s liquidity, direction, and levels of momentum and volatility. See the legend for explanations of the different fields. Market Positive one-year performance UltraShort Nasdaq 100*** UltraShort S&P 500*** UltraShort Russell 2000*** UltraShort Dow 30*** UltraShort Financials*** UltraShort Real Estate*** UltraShort Oil & Gas***

Symbol

Sector

Volume

1-year return

10-day move/rank

20-day move/rank

60-day move/rank

Volatility ratio/rank

QID SDS TWM DXD SK F SRS DUG

Leveraged inverse index Leveraged inverse index Leveraged inverse index Leveraged inverse index Leveraged inverse index Leveraged inverse index Leveraged inverse index

50.74 M 58.46 M 10.03 M 13.28 M 24.87 M 6.06 M 20.32 M

89.27% 68.72% 54.56% 51.21% 46.26% 36.46% 0.24%

-6.28% / 44% -5.96% / 33% -10.13% / 86% -7.23% / 33% -5.21% / 29% -9.38% / 25% -13.00% / 25%

-11.24% / 67% -14.00% / 93% -15.04% / 86% -14.90% / 94% -20.47% / 88% 2.50% / 13% -35.86% / 93%

84.05% / 98% 44.71% / 93% 67.89% / 94% 29.23% / 88% 14.08% / 35% 64.84% / 92% 15.76% / 19%

.66 / 60% .84 / 80% .88 / 75% 1.04 / 83% .89 / 80% 1.18 / 82% .78 / 70%

Leveraged index Leveraged index Leveraged index Leveraged index Index Leveraged index Regional Emerging Markets Regional Financial Regional Energy Financial Index Real Estate Technology Banking Consumer Materials Technology Technology Industrial Retail Index Index Index Index Energy Index Regional Index Metals Utilities Index Energy Energy Retail Metals

121.01 M 15.23 M 48.03 M 74.28 M 44.80 M 13.61 M 26.89 M 132.59 M 7.76 M 226.83 M 19.24 M 12.21 M 8.54 M 35.21 M 21.17 M 15.43 M 10.07 M 8.34 M 17.19 M 16.19 M 15.52 M 7.43 M 288.13 M 11.10 M 10.28 M 478.92 M 54.71 M 118.06 M 41.37 M 7.46 M 7.32 M 9.05 M 40.18 M 10.81 M 4.23 M 8.49 M 18.52 M

-82.24% -71.55% -70.40% -67.23% -63.94% -60.49% -58.26% -56.31% -53.93% -53.68% -50.99% -50.13% -49.95% -49.25% -46.89% -45.51% -43.25% -41.57% -41.08% -40.70% -40.59% -39.97% -38.88% -38.82% -38.33% -37.40% -37.24% -36.19% -35.67% -35.65% -35.25% -33.60% -33.14% -32.93% -27.30% -21.36% -12.12%

-7.29% / 12% 1.03% / 0% -1.78% / 0% -1.61% / 6% -5.65% / 16% -2.92% / 0% 9.33% / 80% 3.12% / 33% -2.15% / 6% -3.66% / 13% -3.17% / 11% 2.15% / 0% -2.22% / 6% -0.07% / 0% -3.11% / 11% -2.18% / 7% -0.75% / 0% 0.78% / 0% 2.26% / 50% -2.53% / 27% 0.64% / 20% 2.36% / 100% 0.23% / 0% 2.43% / 25% -0.22% / 0% -0.91% / 0% 2.26% / 14% 1.22% / 25% -2.16% / 15% 2.91% / 100% 5.54% / 75% -1.35% / 0% -0.98% / 8% -11.40% / 25% 4.89% / 100% 3.30% / 17% 2.22% / 50%

-4.76% / 22% -10.85% / 21% -9.23% / 4% -5.39% / 14% -19.54% / 73% -0.18% / 0% -2.81% / 3% -14.10% / 57% -5.39% / 13% 1.97% / 36% -9.86% / 27% -6.69% / 17% 0.62% / 16% -9.62% / 53% -15.62% / 48% -12.52% / 36% 5.84% / 42% -4.20% / 18% -6.96% / 39% -3.75% / 4% -3.00% / 12% -10.47% / 23% -3.05% / 4% -2.75% / 15% -1.08% / 6% 0.18% / 8% 5.19% / 100% -8.94% / 43% 1.89% / 0% -11.51% / 24% -17.15% / 40% 3.69% / 100% 1.85% / 46% -27.95% / 83% -1.63% / 4% -2.26% / 8% -19.67% / 100%

-60.39% / 96% -63.48% / 89% -63.05% / 100% -54.32% / 98% -47.11% / 96% -47.14% / 97% -49.28% / 84% -44.05% / 92% -38.21% / 94% -32.13% / 95% -41.80% / 98% -50.92% / 87% -30.38% / 94% -34.77% / 95% -41.17% / 98% -40.95% / 100% -16.05% / 43% -31.71% / 98% -38.33% / 95% -34.36% / 100% -33.21% / 97% -32.25% / 95% -35.93% / 99% -35.55% / 97% -29.56% / 98% -29.33% / 97% -35.24% / 86% -33.27% / 97% -24.45% / 88% -29.31% / 87% -33.06% / 71% -25.04% / 84% -24.50% / 95% -46.51% / 97% -25.45% / 23% -24.25% / 100% -11.45% / 71%

.20 / 28% .14 / 8% .17 / 10% .22 / 30% .29 / 13% .29 / 60% .22 / 28% .32 / 38% .26 / 30% .37 / 53% .30 / 67% .17 / 7% .37 / 52% .30 / 62% .30 / 18% .27 / 33% .55 / 75% .38 / 47% .27 / 33% .29 / 38% .31 / 47% .30 / 3% .26 / 17% .31 / 30% .33 / 45% .34 / 42% .27 / 27% .36 / 5% .37 / 82% .32 / 28% .14 / 10% .23 / 25% .45 / 78% .11 / 3% .12 / 47% .43 / 47% .18 / 0%

Negative one-year performance UYG Ultra Financials** DIG Ultra Oil & Gas** QLD Ultra Nasdaq 100** SS O Ultra S&P 500** FXI FTSE/Xinhua China 25 Index DDM Ultra Dow 30** EWZ Brazil EEM Emerging Markets EWH Hong Kong XLF Financial EWT Taiwan OIH Oil Services Dow Jones U.S. Financial Sector IYF EFA EAFE* IYR Dow Jones U.S. Real Estate SMH Semiconductor KBE KBW Bank XLY Consumer Discretionary XLB Materials XLK Technology XLI Industrial XRT Retail QQQQ Nasdaq 100 MDY S&P Midcap 400 Index IVV S&P 500 Index S PY S&P 500 Index XLE Energy IWM Russell 2000 Index EWJ Japan XHB S&P Home Building Index SLV Silver XLU Utilities DIA Dow Jones Industrial Average USO United States Oil Fund UNG U.S. Natural Gas R TH Retail GLD Gold

*Europe, Australasia, Australasia, and the Far East East ** Tracks Tracks twice the move of this index. *** Tracks Tracks twice the inverse, inverse, or opposite, of this index. Legend Vol: 30-day average daily volume, in thousands (unless otherwise indicated). OI: Open interest, in thousands (unless otherwise indicated). 1-year return: The percentage price move from the close one year ago (250 trading days) to today’s close. 10-day move: The percentage price move from the close 10 days ago to today’s close. 20-day move: The percentage price move from the close 20 days ago to today’s close.

59

60-day move: The percentage price move from the close 60 days ago to today’s close. The “rank” fields for each time window (10-day moves, 20-day moves, etc.) show the percentile rank of the most recent move to a certain number of the previous moves of the same size and in the same direction. For example, the rank for 10-day move shows how the most recent 10- day move compares to the past twenty 10-day moves; for the 20-day move, the rank field shows how the most recent 20-day move compares to the past sixty 20-day moves; for the 60- day move, the rank field shows how the most recent 60-day move compares to the past one-

hundred-twenty 60-day moves. A reading of 100 percent means the current reading is larger than all the past readings, while a reading of 0 percent means the current reading is smaller than all previous readings. These figures provide perspective for determining how relatively large or small the most recent price move is compared to past price moves. Volatility ratio/rank: The ratio is the short- term volatility (10-day standard deviation of prices) divided by the long-term volatility (100- day standard deviation of prices). The rank is the percentile rank of the volatility ratio over the past 60 days.


STOCK & FUTURES Snapshot The following tables summarize the trading activity in the most actively traded stocks and futures contracts. The information does NOT constitute trade signals. It is intended only to provide a brief synopsis of each market’s liquidity, direction, and levels of momentum and volatility. Volume figures are for the most-active contract month in a particular market and may not reflect total volume for all contract months. For a more extensive futures snapshot, see Futures & Options Trader magazine (www.futuresandoptionstrader.com). Note: Average volume and open-interest data includes both pit and side-by-side electronic contracts (where applicable). Price activity for CME futures is based on pit-traded contracts, while price activity for CBOT futures is based on the highest-volume contract (pit or electronic). Stock snapshot snapshot as of Nov. Nov. 6

Symbol

Volume

1-year return

10-day move/rank

20-day move/rank

60-day move/rank


MS

61.48 M

-71.61%

-14.88% / 44%

23.61% / 100%

-61.67% / 94%

.16 / 0%

Merrill Lynch

MER

40.89 M

-69.53%

-7.31% / 29%

21.85% / 100%

-36.60% / 62%

.25 / 53%

Vale

RIO

61.50 M

-66.44%

4.63% / 0%

-1.72% / 2%

-53.76% / 86%

.18 / 33%

C

149.13 M

-65.20%

-12.13% / 39%

-10.90% / 42%

-35.32% / 97%

.39 / 43%

Research In Motion

RIMM

37.45 M

-57.64%

3.81% / 33%

-18.75% / 18%

-62.21% / 97%

.12 / 12%

Bank of America

BA C

116.44 M

-54.25%

-12.52% / 36%

2.50% / 16%

-30.28% / 76%

.30 / 43%

Petroleo Brasileiro

PBR

37.43 M

-53.90%

3.11% / 25%

-9.97% / 24%

-51.85% / 88%

.22 / 20%

General Electric

GE

142.72 M

-52.21%

-2.45% / 18%

-3.52% / 16%

-37.43% / 100%

.24 / 43%

EMC Corporation

EMC

38.55 M

-47.41%

11.26% / 43%

0.29% / 0%

-30.15% / 94%

.34 / 62%

Intel

INTC

96.34 M

-44.85%

-4.41% / 25%

-11.09% / 13%

-42.50% / 100%

.28 / 23%

Time Warner

TWX

38.76 M

-44.61%

0.63% / 0%

-5.35% / 5%

-38.47% / 100%

.25 / 2%

Chesapeake Energy

CHK

43.26 M

-43.98%

5.03% / 14%

27.22% / 100%

-52.18% / 74%

.13 / 10%

Cisco Systems

CSCO

84.40 M

-40.73%

-1.74% / 19%

-1.45% / 0%

-30.32% / 100%

.29 / 27%

Apple

AAPL

61.71 M

-40.07%

0.89% / 15%

11.67% / 85%

-44.73% / 95%

.19 / 18%

Microsoft

MSFT

123.32 M

-38.10%

-6.45% / 31%

-6.37% / 44%

-25.19% / 100%

.41 / 27%

AT&T

T

44.32 M

-33.70%

2.89% / 10%

13.00% / 93%

-16.96% / 60%

.48 / 88%

Pfizer

PFE

73.94 M

-28.30%

-4.27% / 27%

4.47% / 59%

-16.65% / 93%

.68 / 82%

Exxon Mobil

XOM

56.50 M

-19.45%

-0.61% / 0%

2.88% / 85%

-10.50% / 48%

.58 / 68%

Oracle Corporation

ORCL

55.20 M

-12.96%

-0.59% / 10%

3.95% / 24%

-26.77% / 100%

.48 / 47%

JPMorgan Chase

JPM

69.50 M

-9.57%

1.08% / 29%

4.31% / 24%

3.66% / 17%

.75 / 68%

Wells Fargo

WFC

66.37 M

-9.13%

-8.17% / 55%

5.58% / 31%

-1.78% / 2%

.49 / 52%

Negative one-year performance Morgan Stanley

Citigroup

Futures snapshot as of Nov. 6

Symbol

Exchange

Volume

OI

10-day move/rank

20 20-day move/rank

60 60-day move/rank


E-Mini S&P 500

ES

CME

3.42 M

2.83 M

-1.17% / 0%

-0.88% / 10%

-29.58% / 98%

.35 / 42%

10-yr. T-note

TY

CME

654.5

1.39 M

-0.10% / 0%

1.75% / 61%

0.02% / 4%

.53 / 48%

E-Mini Nasdaq 100

NQ

CME

498.3

364.9

-1.04% / 0%

-2.48% / 4%

-36.11% / 99%

.28 / 15%

5-yr. T-note

FV

CME

450.5

1.38 M

1.05% / 54%

2.71% / 100%

3.59% / 89%

.61 / 70%

Mini Dow

YM

CME

294.5

99.4

-0.84% / 0%

1.19% / 33%

-24.49% / 95%

.45 / 78%

Crude oil

CL

NYMEX

258.5

243.6

-10.42% / 25%

-29.82% / 85%

-47.61% / 96%

.11 / 3%

30-yr. T-bond

US

CME

239.1

758.5

-0.90% / 27%

0.08% / 0%

0.20% / 11%

.65 / 55%

2-yr. T-note

TU

CME

229.3

729.9

0.80% / 75%

0.97% / 92%

1.91% / 94%

.32 / 48%

E-Mini Russell 2000

TF

ICE

204.3

488.5

1.99% / 33%

1.78% / 22%

-33.53% / 96%

.38 / 8%

Eurocurrency

EC

CME

199.8

154.5

-0.91% / 0%

-7.11% / 81%

-14.70% / 86%

.16 / 3%

Corn

C

CME

128.0

460.7

-3.13% / 19%

-13.74% / 57%

-29.87% / 75%

.14 / 10%

GC

NYMEX

105.9

174.5

2.45% / 100%

-17.41% / 93%

-11.53% / 69%

.16 / 0%

S

CME

84.9

110.4

1.70% / 17%

-8.22% / 33%

-29.59% / 71%

.11 / 7%

Natural gas

NG

NYMEX

61.9

88.9

8.72% / 100%

2.26% / 43%

-17.47% / 16%

.18 / 85%

Wheat

W

CME

36.0

154.0

-0.11% / 0%

-13.60% / 40%

-38.56% / 99%

.16 / 3%

E-Mini S&P MidCap 400

ME

CME

35.4

106.9

2.45% / 25%

-2.04% / 12%

-35.28% / 97%

.32 / 32%

Market

Gold 100 oz. Soybeans

*Average volume and open interest based on highest-volume contract (March 2008). This information is for educational purposes only. Active only. Active Trader Trader provides provides this data in good faith, but it cannot guarantee its accuracy or timeliness. Active timeliness. Active Trader assumes Trader assumes no responsibility for the use of this information. Active information. Active Trader Trader does does not recommend buying or selling any market, nor does it solicit or ders to buy or sell any market. There is a high level of risk in trading, especially for traders who use leverage. The reader assumes all responsibility for his or her actions in the market.


60

THE Economy FIGURE 1: QUARTERLY GDP PERFORMANCE

U.S. economic briefing FED CONTINUES RATE CUTS Meeting: Federal Open Market Committee (FOMC) Date and time: Oct. 29 at 2:15 p.m. Summary: The Fed cut its target fed funds interest rate 0.5 percent to 1 percent, its lowest level in four-and-a-half years. The deepening economic slowdown was attributed mainly to a drop in consumer spending, while the continued weakening of foreign economic activity has hurt exports. The FOMC continues to expect inflation will moderate over the next few quarters as energy and commodity prices stabilize. The following tables compare the S&P 500’s daily and weekly reactions to economic releases as well as historic behavior since 1997 (or earlier). Average Scheduled S&P 500 historical moves rate changes reaction since 1994 -1.11% 0.34% Report day 6.94% 0.15% Five days later

ECONOMY CONTRACTS IN Q3 Report: Gross domestic product for Q3 2007 (adv.) Date and time: Oct. 30 at 8:30 a.m. Actual: -0.3 percent Previous: 2.8 percent Consensus: -0.5 percent

GDP Report day Five days later

S&P 500 reaction 2.58% 2.44%

GDP fell 0.3 percent in the third quarter, according to advance (first) estimates. In addition, revised estimates show GDP dropped dropped 0.2 percent in the fourth quarter of 2007. Source: Bureau of Economic Analysis Seasonally adjusted * Advanced estimate

FIGURE 2: PAYROLLS VS. UNEMPLOYMENT RATE

The unemployment rate has risen 1.7 percent in the last 12 months, an increase of 2.8 million people. Source: Bureau of Labor Statistics

Seasonally adjusted

FIGURE 3: OVERALL VS. CORE INFLATION

Historical moves since 1994 -0.01% 0.35%

CPI UNCHANGED, PPI DECLINES Report: Consumer Price Index (CPI) 8:30 a.m. Date and time: Oct. 16 at 8:30 Actual: 0.0 percent (core 0.1 percent) Previous: -0.1 percent (core 0.2 percent) 61

CPI and PPI year-over-year growth fell in August and September, largely because of dropping energy costs. Source: Bureau of Labor Statistics

Not seasonally adjusted


• January

2009

• ACTIVE TRADER

FIGURE 4: ISM MANUFACTURING INDEX

Consensus: 0.1 percent (core 0.2 percent)

CPI Report day Five days later

S&P 500 reaction 4.25% -0.78%

Historical moves since 1980 0.09% 0.18%

Report: Producer Price Index (PPI) Date and time: Oct. 15 at 8:30 a.m. Actual: -0.4 percent (core 0.4 percent) Previous: -0.9 percent (core 0.2 percent) Consensus: -0.4 percent (core 0.2 percent)

PPI Report day Five days later

S&P 500 reaction -9.03% -4.30%

Historical moves since 1994 0.06% 0.38%

Report: ISM manufacturing index Date and time: Nov. 3 at 10 a.m. Actual: 38.9 Previous: 43.5 Consensus: 42.0 S&P 500 reaction -0.25% -3.61%

Source: Institute of Supply Management

Seasonally adjusted

FIGURE 5: S&P PERFORMANCE The S&P 500 swung swung widly widly in October and early November.

MANUFACTURING INDEX DROPS

ISM manufacturing Report day Five days later

The manufacturing index fell to a 15-year low of 38.9 in October. October.

Source: eSignal

Historical moves since 19 1997 0.29% 0.35%

FIGURE 6: S&P 500 REACTION TO NEWS

UNEMPLOYMENT JUMPS TO 14-YEAR HIGH Report: Employment Nov. 7 at 8:30 a.m. a.m. Date and time: Nov. Non-farm payrolls Actual: -240K Previous: -284K Consensus: -200K Unemployment rate Actual: 6.5 percent Previous: 6.1 percent Consensus: 6.3 percent

Employment Report day Five days later

S&P 500 reaction 2.86% 0.71%


Historical moves since 1994 0.11% -0.22%

2009

•

Most economic releases coincided with large large moves in the S&P 500 in October and November, including a 9.3-percent drop when the PPI report was released on Oct. 15.


62

Key CONCEPTS

At the money (ATM): (ATM): An option whose strike price is identical (or

very close) to the current underlying stock (or futures) price.

The option “Greeks”

Average and median: The mean (or average) of a set of values is the

Delta: The ratio of the movement in the option price for every

sum of the values divided by the number of values in the set. If a set consists of 10 numbers, add them and divide by 10 to get the mean. A statistical weakness of the mean is that it can be distorted by exceptionally large or small values. For example, the mean of 1, 2, 3, 4, 5, 6, 7, and 200 is 28.5 (228/8). Take away 200, and the mean of the remaining seven numbers is 4, which is much more representative of the numbers in this set than 28.5. The median can help gauge how representative a mean really is. The median of a data set is its middle value (when the set has an odd number of elements) or the mean of the middle two elements (when the set has an even number of elements). The median is less susceptible than the mean to distortion from extreme, non-representative values. The median of 1, 2, 3, 4, 5, 6, 7, and 200 is 4.5 ((4+5)/2), which is much more in line with the majority of numbers in the set.

point move in the underlying. An option with a delta of 0.5 would move a half-point for every 1-point move in the underlying stock; an option with a delta of 1.00 would move 1 point for every 1-point move in the underlying stock.

Bollinger Bands: Bollinger Bands are a type of trading “envelope”

consisting of lines plotted above and below a moving average, which are designed to capture a market’s typical price fluctuations. The indicator is similar in concept to the moving average envelope, with an important difference: While moving average envelopes plot lines a fixed percentage above and below the average (typically three percent above and below a 21-day simple moving average), Bollinger Bands use standard deviation to determine how far above and below the moving average the lines are placed. As a result, while the upper and lower lines of a moving average envelope move in tandem, Bollinger Bands expand during periods of rising market volatility and contract during periods of decreasing market volatility. volatility. Bollinger Bands were created by John Bollinger, CFA, CMT, the president and founder of Bollinger Capital Management (see Active Trader, Trader, April 2003, p. 60). By default, the upper and lower Bollinger Bands are placed two standard deviations above and below a 20-period simple moving average. Upper band = 20-period simple moving average + 2 standard deviations Middle line = 20-period simple moving average of closing prices Lower band = 20-period simple moving average - 2 standard deviations

Bollinger Bands highlight when price has become high or low on a relative basis, which is signaled through the touch (or 63

Gamma: The change in delta relative to a change in the under-

lying market. Unlike delta, which is highest for deep ITM options, gamma is highest for ATM options and lowest for deep ITM and and OTM options. options. Rho: The change in option price relative to the change in the

interest rate. Theta: The rate at which an option loses value each day (the

rate of time decay). Theta is relatively larger larger for OTM than than ITM options, and increases as the option gets closer to its expiration date. Vega: How much an option’s price changes per a one-percent

change in volatility.

minor penetration) of the upper or lower line. However, Bollinger stresses that price touching the lower or upper band does not constitute an automatic buy or sell signal. For example, a close (or multiple closes) above the upper band or below the lower band reflects stronger upside or downside momentum that is more likely to be a breakout (or trend) signal, rather than a reversal signal. Accordingly, Accordingly, Bollinger suggests using the bands in conjunction with other trading tools that can supply context and signal confirmation. Bootstrapping: A method for estimating results from a data set by

creating multiple series of random samples and comparing comparing them to the original set. This approach is used to confirm the statistical significance of back-tested performance. Moving average convergence-divergence (MACD): Although Although it is often

grouped with oscillators, the MACD is more of an intermediateterm trend indicator (although it can reflect overbought and oversold conditions). The default MACD line (which can also be plotted as a histogram) is created by subtracting a 26-period exponential moving average (EMA) of closing prices from a 12-period EMA of closing prices; a nine-period EMA is then applied to the MACD line to create a “signal line.” www.activetradermag.com

• January

2009

• ACTIVE TRADER

True range is the greatest (absolute) distance of the following: MACD = EMA(C,12)-EMA(C,26) Signal line = EMA(MACD,9) Out of the money (OTM): A call option with a strike price above the

price of the underlying instrument, or a put option with a strike price below the underlying instrument’s price. True range (TR): A measure of price movement that accounts for

the gaps that occur between price bars. This calculation provides a more accurate reflection of the size of a price move over a given period than the standard range calculation, which is simply the high of a price bar minus the low of a price bar. The true range calculation was developed by Welles Wilder and discussed Trading Systems (Trend in his book New Concepts in Technical Trading Research, 1978). True range can be calculated on any time frame or price bar — five-minute, hourly, daily, weekly, etc. The following discussion uses daily price bars for f or simplicity. simplicity.


2009

•


1. Today’s high and today’s low. 2. Today’s high and yesterday’s close. 3. Today’s low and yesterday’s close. Average Average true range (ATR) is simply a moving average of the true range over a certain time period. For example, the five-day ATR ATR would be the average of the true range calculations over the last five days. Volatility: The level of price movement in a market. Historical

(“statistical”) volatility measures the price fluctuations fluctuations (usually calculated as the standard deviation of closing prices) over a certain time period — e.g., the past 20 days. Implied volatility is the current market estimate of future volatility as reflected in the level of option premiums. The higher the implied volatility, volatility, the higher the option premium.

64

TRADING Resources

NEW PRODUCTS & SERVICES The Quote.com team at eSignal has redesigned RagingBull.com. The revamp includes new navigation tabs and content placement as well as access to real-time quotes. The redesigned site includes a discussion search tool to find archived keywords, member names, board names, data ranges, and the latest relevant discussions; the ability to share favorite members’ lists and forum lists; and market screeners that allow users to join the latest talk about stocks using 24 different criteria on five exchanges. For more information, visit www.RagingBull.com. www.RagingBull.com.

service allowing trades to be automatically executed when atrisk stock and ETF prices fall enough to trigger their daily SmartStop. Smartstops.net has teamed up with TD Ameritrade, offering free subscriptions to the firm’s 6.8 million customer accounts. Calculated daily on most U.S.-listed stocks and ETFs, SmartStops are based on an approach that considers current technical indicators, historical trends, and a combination of exit methodologies optimized for the prevailing market direction. BarclayHedge and Global Fund Technologies, LLC announced the

Adaptrade Software’s Market System Analyzer (MSA) version 3 is

available. MSA software for futures and stock traders applies position sizing, Monte Carlo analysis, dependency analysis, equity curve crossover trading, and other money-management methods. Version 3 includes full portfolio analysis, portfolio optimization, correlation analysis, support for non-US traders, and more. The software works with any trading system or method and requires only a list of profits and losses as input. An EasyLanguage interface to TradeStation is included. A 30-day trial can be downloaded from www.Adaptrade.com. www.Adaptrade.com.

launch of MyFundFinder.com, a capital introduction platform designed to match hedge fund managers with institutional and high net worth investors. MyFundFinder.com is a web-based platform designed to provide hedge-fund managers with a capital-raising tool and to provide investors free access to search online through more than 1,900 hedge funds, funds of funds, and managed futures funds (CTAs) to discover, match, and connect with those that meet their investment needs. Additional platform features include industry discussion forums, geographical mapping, and new fund launches, all centered on a community-driven site.

Vhayu Technologies has partnered with Alphacet, Inc., a developer

of software for quantitative analysts, portfolio managers, and traders, to provide customers with an integrated tick database and alpha generation solution. It enables quants to create, backtest, and analyze multi-layer models in hours-to-days instead of weeks-to-months. This partnership combines Vhayu Velocity, Velocity, which can process, analyze, and store tick and bar data, with Alphacet Explorer, a codeless historical backtesting engine designed specifically for Vhayu Velocity for use across asset classes and instrument types. Option-industry denizen and author Dan Passarelli launched a new mentoring company designed to educate option traders. Market Taker Mentoring (http://markettaker.com) offers an educational service to do-it-yourself traders as well as seasoned professionals. Passarelli’s new organization takes a personal approach to mentoring. In the six-week course, students receive one-on-one time with Passarelli in a program tailored to their specific educational levels. For more information and a free Greeks, visit excerpt from Passarelli’s book Trading Option Greeks, http://markettaker.com/FREE_Book_Excerpt_.html. Smartstops.net has introduced BrokerLink, a portfolio-protection

65

HedgeCo Networks, LLC has launched its online analytical and

reporting tool, the Hedge Fund Calculator. Available as a monthly or annual subscription service, the Hedge Fund Calculator was designed for hedge funds and funds of hedge funds, and facilitates the computation of quantitative statistics, net performance numbers, and the creation of branded marketing materials. Key features of the Hedge Fund Calculator include: online access, branded and customized tearsheets, a contact manager, and benchmark analysis. To view a demo or sign up for a free Webinar, Webinar, visit HedgeFundCalculator.com. Dow Jones has signed a strategic alliance with Agencia EFE to

develop a joint Spanish-language news service — EFE Dow Jones News — to serve financia l professionals, corporations, media, institutions, and private investors in Spain. The new realtime newswire will draw upon coverage of Spanish companies and policy-making in EFE’s economic service, EFECOM, and the international financial and market reporting of Dow Jones en Español to offer clients expanded coverage of Spanish business, including regional reporting and analysis of small- and mid-cap stocks. For more information about Dow Jones Newswires, visit www.dowjonesnewswires.com.


• January

2009

• ACTIVE TRADER

Deutsche Bank’s retail online foreign exchange trading platform,

Cognotec has partnered with Market News International (MNI) to

dbFX.com, has introduced decimalised pricing on its foreign exchange prices. Also known as fractional pips, all prices on the dbFX.com platform are now provided in tenths of a pip. Launched in 2006, dbFX.com is available in multiple languages, has 34 currency pairs, and is accessible in more than 70 countries around the world.

enable access to forex market news from around the world. Users of Cognotec RealStream Margin trading solution can now access MNI’s FX Bullet Points newsfeed on their desktops from within the RealStream Margin trading platform. continued on p.

6 7 6 7

BOOKSHELF Stock Trader’s Almanac 2009

The Art of the Trade: Trade: What I Learned (and Lost) Trading the Chicago Futures Markets

By Jeffrey A. Hirsch and Yale Hirsch Wiley, Wiley, 2009 Hardcover, Hardcover, 193 pages $39.95 This annual almanac, first published in 1967, is composed of years of market history arranged on a calendar. It analyzes cycles and patterns in the stock market and examines seasonal tendencies. This trove of yearly, monthly, weekly, daily, and intraday data stretches back for decades, highlighting a wide range of best and worst performances. It offers event-specific studies such as post-election and end-of-quarter data, and analyzes many market maxims such as the January barometer and the Santa Claus rally. The Stock Market Philosopher: Insights of a Soviet-Born New York-Bred Hedge Fund Trader

By Gennady Favel W&A Publishing, 2008 Hardcover, Hardcover, 142 pages $19.95

This book is a reworking of Jankovky’s first book Dancing With Lions published under the pseudonym “Trader X.” Drawing upon more than 20 years in the futures and options business, Jankovsky recounts his journey to success, clawing his way through the Chicago financial ecosystem. Through his account, Jankovsky exposes the seedy underbelly of an industry where “drug use, financial irresponsibility, and personal vendettas are commonplace.” Keynes and the Market: How the World’s Greatest Economist Overturned Conventional Wisdom and Made a Fortune on the Stock Market

By Justyn Walsh Wiley, Wiley, 2008 Hardcover, Hardcover, 209 pages $27.95

This book provides a look at one man’s path from young immigrant to hedgefund trader. Favel writes about the markets from his own perspective, drawing on his experiences growing up in the Soviet Union trading Bazooka Joe gum wrappers, his young-adulthood trading comic books and gambling, and on through college and his professional career. He discusses how his experiences have shaped his view of the markets and offers insights into how they work.


By Jason Alan Jankovsky Wiley, Wiley, 2008 Hardcover, Hardcover, 183 pages $29.95

2009

•


Walsh’s book looks at the life and theories of famed economist and profitable stock trader John Maynard Keynes. The author looks at Keynes’ methods to see why he was so successful, how investors like Warren Buffet have adapted his principles, and how average traders can benefit from his methods in today’s markets.

66

Trading Resources continued

ICAP has launched its Global Currency Data Feed, a proprietary

feed of real time streaming prices from a selection of sources, including ICAP’s electronic spot FX broking platform EBS and ICAP’s internal pricing systems. The feed comprises prices for more than 155 currency pairs and cross currency pairs from more than 180 countries. Market participants can obtain the data feed via direct connection or selected vendor partners. ICAP Market Information and Commentary offerings include real-time, end-of-day, and historical market data, as well as research and commentary from economists and analysts.

tion and engineering, construction machinery, construction materials, diversified metals and mining, heavy electrical equipment, industrial machinery, and steel. CQG, Inc., the charting, analytics, and trade-routing platform for global electronically traded futures markets, has added SEB Futures to its list of Futures Commission Merchant (FCM) part-

ners. CQG has teamed with SEB to connect traders to Euronext, Globex, ICE, and Eurex. Traders clearing through SEB have access to CQG’s market analysis tools and advanced order execution software.

Wave59 Technologies released Wave59 RT 3.0, an update of its

real-time technical market analysis program. Version 3.0 includes the ability to design, backtest, optimize, and automate custom trading systems using Wave59’s QScript language. Wave59 RT RT is a charting and analysis program designed around versions of classical technical tools, as well as a suite of proprietary algorithms. For additional information on Wave59 RT 3.0, contact Jonn Millarkie at (866) 494-7613 or visit www.wave59.com to download a 30-day free trial. CME Group and BM&FBOVESPA announced the order routing of

BM&F derivatives products on CME Globex. The order routing linkage enables customers using the CME Globex electronic trading platform to trade BM&FBOVESPA BM&FBOVESPA products directly, directly, including futures and options on one-day Inter-Bank Deposits, the Bovespa Stock Index (pending regulatory approval), and commodities such as Arabica coffee, live cattle, and corn. BM&FBOVESPA customers will have the ability to trade CME Group products directly through their BM&FBOVESPA connections, including CME Group futures and options on interest rates, equity indices, foreign exchange, commodities, and energy and metals products. More information on the agreement can be found at a t www.cmegroup-bmfbovespa.com. www.cmegroup-bmfbovespa.com. CME Group also has launched the latest version of CME E-quotes, a real-time streaming market data application offering quotes, charting, advanced analytics, and news on CME Group-traded products, including interest rates, equity indices, foreign currencies, commodities, energy, metals, and alternative investments. It also offers access to prices for products listed on the Minneapolis Grain Exchange and the Kansas Board of Trade, which are available for electronic trading on CME Globex. For more information and a free twoweek trial, visit www.cmegroup.com/e-quotes. www.cmegroup.com/e-quotes. Invesco PowerShares Capital Management LLC has listed an

emerging markets infrastructure portfolio on NYSE Arca. The PowerShares Emerging Markets Infrastructure Portfolio (PXR) is an exchange-traded fund (ETF) based on the S-Network Emerging Infrastructure Builders IndexSM. The index is designed to measure the overall performance of securities of companies involved in infrastructure construction and development in emerging market countries. Industries include construc67

optionMONSTER introduced trade MONSTER, an online brokerage

designed by professional traders for self-directed investors. Cofounded by Jon “DRJ” Najarian and Pete Najarian, the optionMONSTER group of companies provides tools and education for individual investors in options and stock markets. trade MONSTER allows you to customize how trade, position, and market information is displayed. trade MONSTER’s educational content is embedded throughout the site and ranges from basic glossaries to detailed discussions of sophisticated option strategies. In addition, trade MONSTER offers webinars from the Najarians and invited guests. FX Solutions, LLC (www.fxsolutions.com) (www.fxsolutions.com) announced its merger with IFX Markets Inc. Both companies are wholly owned sub-

sidiaries of City Index Group. IFX Markets customer accounts will transfer to FX Solutions, which provides foreign exchange trading capabilities to retail customers, introducing brokers and white label partners in more than 50 countries worldwide. IFX Markets customers who trade on the GTS platform will find features such as fixed spreads, streaming interbank market prices, automatic execution, multiple order types, and integrated risk management allowing up to five stops and limits per order, including trailing stops. John Bollinger’s Bollinger’s BBForex.com, which provides Bollinger Band analytics for the forex community, has a new feature merging technical analysis with forex news from various news publishers. Users can monitor forex charts and the latest news relating to specific symbol pairs as it occurs. To assist new forex traders, a basics section has also been added. It provides general forex information, currency pricing factors, forex trading instruments, investment common sense, and a forex glossary. The Web site is free. Trading Resources is a forum for industry businesses to announce new products and upgrades. Listings are adapted from company press releases and are not endorsements or recommendations from the Active Trader Magazine Group. E-mail press releases to [email protected] [email protected]. m. Publication is not guaranteed.


• January

2009

• ACTIVE TRADER

Web WATCH

Web Watch: Collective2.com REVIEWED BY ACTIVE TRADER STAFF STAFF

C

ollective2.com tracks the performance of

FIGURE 1: PORTFOLIO MAKER

thousands of trading systems. System developers publish their systems on the site, which enables people to “subscribe” to

systems on a case-by-case basis. Developers can provide as little or as much information as they like about their trade rules, but for subscribers the systems are essentially “black boxes” — opaque instructions telling them when to trade. The site provides equity curves and performance statistics calculated using live quotes. Along with statistics such as average trade length, profitability over time, and win percentage, Collective2 also calculates each system’s “realism factor,” which it says indicates how likely hypothetical results are to be repeated in real-world trading. This includes factors such as slippage, trade size, and liquidity. Collective2 tracks stock, futures, options (but not

The order entry window resembles an online broker’s broker’s entry window and sends trade signals directly to subscribers. Source: Collective2.com

options on futures), and currency systems. After someone subscribes to a system, the vendor sends trade signals to

free trial periods. Subscribers pay in one of three ways: a recur-

the site for subscribers to act upon. They can also send alerts to

ring charge, a charge on profitable periods, or a charge on indi-

subscribers regarding market conditions or advising them to be

vidual profitable trades.

prepared for upcoming trades.

Collective2 takes 30 percent of all subscription fees. Also, sys-

Figure 1 shows sh ows Collective2’s Collective2’s order entry window, window, which han-

tem designers pay the site $98 every six months to publish an

dles stop and limit orders and more advanced order types.

initial system, with a reduced fee for additional systems. But

System designers can use the order entry screen to post signals

designers can post a system and enter up to five trade signals for

or, alternately, alternately, send signals directly to subscribers from plat-

free.

forms such as TradeStation, TradeBullet, TradeBullet, Interactive Brokers, MetaTrader, MetaTrader, and NinjaTrader. NinjaTrader. In addition, more advanced programmers can trade signals directly to the site using

After a system is registered, designers can see who has paid, when they paid, and when the next payment is due. Almost every section of the site includes inc ludes detailed, step-by-

Collective2’s signal entry application programming interface

step instructions, and some sections also include instructional

(API).

videos. Many pages are accompanied by a small window offer-

Subscription fees are determined by the designers; some offer ACTIVE TRADER • January

2009

•


ing advice or helpful links. 68

January 2009

TRADING Calendar

LEGEND CPI: Consumer price index ECI: Employment cost index FDD (first delivery delivery day): day): The first day on which delivery of a commodity in fulfillment of a futures contract can take place. FND (first notice day): Also day): Also known as first intent day, this is the first day on which a clearinghouse can give notice to a buyer of a futures contract that it intends to deliver a commodity in fulfillment of a futures contract. The clearinghouse also informs the seller. FOMC: Federal Open Market Committee

1

FDD: January crude oil, natural gas futures (CME)

2

December ISM manufacturing report silver, and copper futures (CME) FDD: January gold, silver,

3 4 5

December employment report November construction spending December ISM non-manufacturing report FND: January heating oil and RBOB gasoline futures (CME)

6

November factory orders

7

GDP: Gross domestic product ISM: Institute for Supply Management LTD (last trading day): The final day trading can take place in a futures or options contract. PMI: Purchasing managers index

8 9

November wholesale inventories FDD: January heating oil and RBOB gasoline futures (CME) LTD: January currency options

10

PPI: Producer price index Quadruple witching Friday: A Friday: A day where equity options, equity futures, index options, and index futures all expire.

CME: Chicago Mercantile Exchange

11 12 13

November trade balance

14

November business inventories December retail sales LTD: February crude oil options (CME)

15

December PPI

OC: OneChicago

16 S

M

T

W

T

F

S

28

29

30

31

1

2

3

4

5

6

7

8

9

10 10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

17 18 19 20

69

December CPI December production and capacity utilization January U of M consumer sentiment ( prelim.) LTD: January equity and index options; January single stock futures (OCX)

LTD: February crude oil futures (CME) www.activetradermag.com • January 2009 • ACTIVE TRADER

Report times

21

Economic release

22

December housing starts FND: February crude oil futures (CME)

23

LTD: February treasury options (CME)

24 25 26

December existing home sales

27

silver, and copper LTD: February natural gas, heating oil, gold, silver, options (CME)

28 29 30

silver, and copper futures (CME); February LTD: January gold, silver, natural gas futures (CME) December durable goods December new home sales FND: February natural gas futures (CME) Q4 GDP (adv.) Q4 employment cost index January U of M consumer sentiment ( final) January Chicago PMI FND: February gold, silver, and copper futures (CME) LTD: February heating oil and RBOB gasoline futures (CME)

31 February 1 2 3 4 5 6

FDD: February crude oil, natural gas futures (CME) January ISM manufacturing report December personal income silver, and copper futures (CME) FDD: February gold, silver,

Release time (ET)

GDP

8:30 a.m.

CPI

8:30 a.m.

ECI

8:30 a.m.

PPI

8:30 a.m.

Productivity and costs

8:30 a.m.

Employment

8:30 a.m.

Personal income

8:30 a.m.

Business inventories

8:30 a.m.

Durable goods

8:30 a.m.

Retail sales

8:30 a.m.

Trade balance

8:30 a.m.

Housing starts

8:30 a.m.

Chicago Fed national activity index

8:30 a.m.

Production & ca c apacity utilization

9:15 a.m.

Leading indicators

10 a.m.

Consumer confidence

10 a.m.

Univ. of Michigan consumer sentiment

10 a.m.

Wholesale inventories

10 a.m.

Philadelphia Fed survey

10 a.m.

Existing home sales

10 a.m.

Construction spending

10 a.m.

Chicago PMI re report

10 a.m.

ISM report on business

10 a.m.

ISM non-manufacturing report

FND: February heating oil and RBOB gasoline futures (CME) January ISM non-manufacturing report Q4 productivity and costs (prelim.) January employment report

on business

10 a.m.

New home sales

10 a.m.

Factory orders

10 a.m.

Federal budget

2 p.m.

Consumer credit

3 p.m.

The information on this page is subject to change. Active change. Active Trader Trader is is not responsible for the accuracy of calendar dates beyond press time.


70

UPCOMING Events

ADVERTISING Index Advertiser

Event: The Options Intensive Two-day Seminar Date: Dec. 4 Location: CBOE Options Institute, Chicago For more information: www.cboe.com Event: Dynamic Hedging of Long Volatility Strategies

Ablesys www.ablesys.com Active Trader Trader Bookstore www.invest-store.com/activetradermag

Date: Dec. 4-5

CME CM E Gr Grou oup p

Location: Sheraton Suites on the Hudson, New York

www.cmegroup.com/tradeforex

For more information: www.marcusevans.com Deutsche Bank Event: The World Money Show Date: Feb. 4-7 Location: Orlando Date: March 17-19 Location: Hong Kong Date: May 11-14 Location: Las Vegas

www.dbfx.com/at eSignal www.esignalondemand.com

For more information: Go to www.moneyshow.com and

Fidelity

click on “Events”

www.fidelity.com

Event: International Trader’s Expo

Forex.com

Date: Feb. 21-24

www.forex.com

Location: New York, New York For more information: www.tradersexpo.com Event: 25th Annual Risk Management Conference Date: March 8-10

FXCM www.fxcm.com/fss.html Interactive Brokers www.tradersexpo.com

Location: The Ritz-Carlton, Laguna Niguel, Dana Point, Calif. For more information: www.cboermc.com

MB Trading www.mbtrading.com

Event: Live Trading Software and Trading Expos Date: April 5-7 Location: Miami Date: April

PFG PF G Be Best st

Date: June Date: June 7-9 Location: Houston

www.pfgbest.com/webseminar

For more information: http://livetradingexpo.com

TD AMERITRADE

Event: The 15th Forbes Cruise for Investors

www.tdameritrade.com

Date: June Date: June 2-14

Track ‘N Trade

Location: Lisbon to Venice

www.trackntrade.com

For more information: Go to www.moneyshow.com and click on “Events”

TradeStation www.tradestation.com

Event: International Trader’s Expo Date: June Date: June 3-6 Location: Los Angeles For more information: www.tradersexpo.com

Trade The News www.tradethenews.com Wealth Lab www.wealth-lab.com

71


TRADE Diary

A hard-hit hard-hit — but but still still standing standing — banking stock is available at a deep discount.

TRADE Date: Oct. 6-10. Entry: Long Citicorp (C) at an average price of 14.68. Reason(s) for trade/setup: This long-term investment position was taken because of the broader market meltdown, the especially bad meltdown in banking stocks, and the fact that C had survived the banking purge that culminated around the time the government’s financial bailout plan was announced. Furthermore, C took an extra stumble after it lost a fight with Wells Fargo to acquire another failed bank, Wachovia, allowing the opportunity to buy shares at an immediately discounted price (less than a third of where they were a year ago). Initial stop: N/A. Initial target: N/A.

RESULT Exit: Position still open. Profit/loss: -3.16 (21.5 percent). Trade executed according to plan? Yes. Outcome: Down approximately 9 percent on Oct. 28, this position has actually fared better than any of the other

Source: TradeStation TradeStation

stocks we’ve picked up recently at “bargain” prices. Such moves have to be put into perspective given the historic nature of the current market, though — at one point the position was up 17 percent. The last few bars of the weekly chart inset hint at the extreme volatility that preceded and followed this trade. Buying a banking stock is indeed a gamble — the discount at which we purchased C testifies to the extent the market fears them — but C (along with JPMorgan Chase and Bank of America) survived the October massacre, and an d we put on a relatively small position to hold as an investment. In the short-term, the position is a disaster. On a decade or longer time frame, the statistics indicate the purchase price will be quite favorable. That, anyway, anyway, is the rationale.  Note: Initial targets for trades are typically based on things such as the historical performance of a price pattern or trading system signal. However, individual trades are a function of immediate immediate market behavior; initial price targets are flexible and are most often used as points at wh ich a portion of t he trade is liquidated to reduce the position’s open risk. As a result, the initial (pre-trade) reward-risk ratios are conjectural by nature.

Trade Summary Date 10/6/08

Stock

En Entry

Initial stop

Initial target

IRR

MTM

Date

P/L

LOP

LOL

Length

C

16.34

N /A

N/A

N/A

11.52

11/6/08

-3.16 (21.5%)

2.57

-2.68

8 days

10/7/08

15.50

10/10/08

13.45

Legend — IRR: initial reward/risk ratio (initial target amount/initial stop amount). LOP: largest open profit (maximum available profit during lifetime of trade). LOL: largest open loss (maximum potential loss during life of trade). MTM: Marked to market (trade’s open profit or loss at a given time).


2009

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72

TRADE Diary Volatile conditions call for cautious trading. TRADE Date: Monday, Oct. 20. Entry: Long the S&P 500 tracking stock (SPY) between 94.90 and 95.80. Reason(s) for trade/setup: With the market having bounced (on Oct. 16) after making a semichallenge to the Oct. 10 low, SPY is poised to follow through on Friday’s “stealth” up day — higher low, higher high, and slightly lower close. The goal is to play the day from the long side, taking small profits in stages, raising stops quickly to remove risk, and re-entering on additional pullbacks as appropriate. We initially bought at three prices — 95.80, 95.20, and 94.90 — as price was moving down after a strong open.

Source: TradeStation TradeStation

Trade executed according to plan? Yes.

We We caught a good point — after af ter the smallest of dips below the entry price the market turned up, making only one notable pullback for the remainder of the session. We took off part of the new trade at the secondary target (96.80), raised the stop to 95.88, and put in an order to sell another portion at 97.75 — a level we thought had only a small chance of getting hit. The market ultimately blew through that level, and we held the remainder of the position overnight. Instead of following through the next day, though, the market turned back down, stopping out the remainder of the trade. Looking at the chart may leave the impression we could have saved ourselves a lot of trouble by not raising stops and holding the initial position longer, but this is only obvious in hindsight. Anyone who has been in the market lately knows this kind of day has been the exception to the rule — sharp intraday retracements are de rigueur on most up days, and down days have been more prevalent in general.

Outcome: Not executed perfectly, to be sure, but one of the more satisfying days recently. recently. After taking partial p rofits at 96.46, we raised the stop to above breakeven (at 95.73) for the entire three-part initial position. The stop was hit, but when the market failed to follow through, we re-entered at 95.65.

Note: Initial targets for trades are typically based on things such as the historical performance of a price pattern or trading system signal. However, individual trades are a function of immediate market behavior; initial price tar gets are flexible and are most often used as points at which a portion of the trade is liquidated to reduce the position’s open risk. As a result, the initial (pre-trade) reward-risk ratios are conjectural by nature.

Initial stop: 93.04, 1.31 below the morning’s swing low. Initial target: 96.46. Second target: 96.80.

RESULT Exit: Multiple exits — see summary table. Profit/loss: +5.27.

Trade Summary S ummary Date Stock 10/20/08 SPY

Entry 95.80 95.20 94.90 95.65

Initial stop 93.04

Initial target 96.46

96.80

IRR 0.24 0.58 0.84

Exit 96.46 95.73 95.73 96.80 97.75

Date 10/20/08

10/21/08

P/L +0.66 (0.69%) +0.53 (0.56%) +0.83 (0.87%) +1.15 (1.2%) +2.10 (2.2%)

LOP 3.31

LO LOL Length -0.55 4-5 hours

3.46

-0.11

1 days

Legend — IRR: initial reward/risk ratio (initial target amount/initial stop amount). LOP: largest open profit (maximum available profit during lifetime of trade). LOL: largest open loss (maximum potential loss during life of trade). 73


• January

2009

• ACTIVE TRADER

At January 2009 Issue

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