S&C 03-2019.pdf

THE TRADERS’ MAGAZINE SINCE 1982

THE 21ST-CENTURY COVERED CALL How to kill two birds How with one option

8

DOES HISTORY REPEAT REPEA T ITSELF? Looking for time-based time-ba sed patterns for a trading trad ing edge 12

TRADING THE FAKEOUT Keep an eye on these Keep winning patterns

18

INTERVIEW Claudio Demb and the psychology of trading

34

BREAKAWAY GAPS Testing them for reliability relia bility and proftability 38

MARCH 2019

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CONTENTS

MARCH 2019, VOLUME 37 NUMBER 3

7 Daytrading Pivot Channels The Traders’ MagazineTM EDITORIAL

[email protected] Editor in Chief Jack K. Hutson Editor Jayanthi Gopalakrishnan Production Manager Karen E. Wasserman Art Director Christine Morrison Graphic Designer Wayne Shaw Webmaster Han J. Kim Contributing Editors John Ehlers, Anthony W. Warren, Ph.D. Contributing Writers Thomas Bulkowski, Martin Pring, Barbara Star, Markos Katsanos

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http://www.traders.com Staff members may be emailed through through the Internet using rst initial plus last name plus @traders.com Authori Authoriza zation tion to photo photocopy copy items for internal internal or personal personal use, or the internal internal or personal personal use of specic specic clients, clients, is granted by Techni Technical cal Analy Analysis, Inc. for users regis registered tered with the Copy Cop yright Clearance Clearance Center Center (CCC) Transactional Reporting Service, Serv ice, provided provided that the base fee of $1.00 per copy, plus 50¢ per page is paid directly to directly to CCC, 222 Rosewood Drive, Drive, Danvers, MA 01923. Online: http://www http://www.copyright.com. .copyright.com. Fo Forr those organi organiza zations tions that have been granted a photocopy license by CCC, a sepa separate system system of payment payment has been arranged. The fee code for users of the Transactional Reporting Service Service is: 0738-3355/2019 $1.00 + 0.50. (13 issues) $89.99; Subscrip Sub scriptions: tions: USA: one year (13 Magazines shipped outside the US require additional postage as follows: Canada, US$15 per year; Europe, US$25.50 per year; all other countries US$39 per year. Single Sin gle copies of most past issues from the current current year are availa avail able prepaid prepaid at $8 per copy. Prior years are availa available in book format (without ads) or digitally from www.traders. com. USA funds only. Washington state resi residents add sales tax for their locale. VISA, MasterCard, AmEx, and Discover accepted. Subscription orders: 1 800 832-4642 or 1 206 938-0570. Technical Analysis of STOCKS & COMMODITIES™, The Traders’ Magazine™, is prepared from information believed to be reliable but not guaranteed by us without without further verication, and does not purport to be complete. Opinions expressed are subject to revision without noti-

by Ken Calhoun Does “intraday swing trading” sound like a contradiction in terms? Well, We ll, it may actually not be because it combines the best of both worlds worlds.. Find out how this approach can solvee some of t he trouble spots of solv both daytrading and swing trading and ultimately boost prot potential.

INTERVIEW

34 The Psychology Of Trad Trading ing With Claudio Demb by Jayanthi Gopalakrishnan Claudio Demb, MD, is a psychiatrist and has been an individual trader since the 1990s. He is a frequent contributor to this magazine. Along with his professional practice, he has an academic appointment as an instructor in psychiatry at Harvard Medical School. We spoke with him about how he juggles trading and a full-time job, and how he uses his insights into trading psychology to improve his own trading.

8 The 21st-Century Covered Call by Robert J. Seifert Are you tired of writing covered calls only to see your stock get called away as it heads into the stratosphere? Here is a strategy that professional traders use to kill two birds with one option.

38 Tr Trading ading Breakaway Gaps by Pawel Kosinski Many traders like to trade breakaway gaps. How effective are they? Here, we look at backtesting results of trading different breakaway gaps to determine if they can be p rotable.

FEATURE ARTICLE

12 Does History Repeat Itself In The Markets? by Alessandro Aldrovandi, Max Malandra, & Fabio Pacchioni Seasonality or repeating patterns in nancial data can come in many shapes and sizes and can put the probabilities on your side. Or does general market unpredictability ultimately undermine that edge? Here are some ideas on looking for time-based patterns and an example of how to backtest their reliability.

41 Futures For You by Carley Garner Here’ss how the futu res market Here’ really works.

42 Sector-Rotation ETFs Underperform by Leslie N. Masonson Rotating into leading sectors while switching to a defensiv defensivee position in downturns is an ideal tactic if it can be implemented successfully, but can it? Are there any ETFs that have succeeded with it? If there are, they could save you the work of implementing the approach yourself, so we’ll i nvestigate.

18 Trading The Fakeout by Fawad Razaqzada Can you prot from fa keouts? Here’ss one trader’s Here’ t rader’s take on how to identify these patterns and trade them protably.

25 Algo Q&A by Kevin J. Davey Got a question about system or algo trading?

46 Explore Your Options by Jay Kaeppel Got a question about options?

26 All About OBV by John Devcic On-balance volume is a classic indicator that can be helpful for indicating trends and for conrmi ng other indicators. i ndicators. You’ve You’ve undoubtedly looked at it on your charts, but if you’ve you’ve never really known exactly how it works or how it’ss most useful, here’s a close-up it’ view.

60

Trading Tr ading Perspectives by Rob Friesen Some perspectives on the equities world.

DEPARTMENTS 6 Letters To S&C 48 Traders’ Tips





























The editors of S&C invite readers to submit their opinions and information on subjects relating to technical analysis and this magazine. This column is our means of communication with our readers readers.. Is there something you would like to know more (or less) less) about? Tell Te ll us about it. Without a source of new ideas and subjects coming f rom our readers, this magazine would not exist. Email your correspondence to to Editor@ [email protected] or address or address your correspondence to: Editor, Stocks & Commodities, 4757 California Ave. SW, SW, Seattle, WA 98116-4499. All letters become the propert y of Technical Technical Analys is, Inc. Letter-writers must include their fu ll name and address for vericat ion. Letters may be edited for length or clarity. The opinions expressed in this column do not necessarily represent represent those of the magazine.—Editor

script LeavittProjection{ input y = close; input n = 20; rec x = x[1] + 1; def a = (n * sum(x * y, n) - sum(x, sum(x , n) * sum(y, n) ) / ( n *sum(Sqr(x), n) - Sqr(sum(x, n))); def b = (sum(Sqr(x), n) * sum(y, n) - sum(x, n) * sum(x *y, n) ) / ( n * sum(Sqr(x), n) Sqr(sum(x, n))); plot LeavittProjec tion= a*x+ b; }

LEAVITT CONVOLUTION

script LeavittConvolution { input price = close; input n = 20; def intLength = Floor(Sqrt(n)); Floor(Sqrt(n));

indicator; I would be very interested in an Editor, indicator that outperforms the HMA. I read with interest Jay Could you either share or direct me to Leavitt’s article in the a place where I might be able to obtain January 2019 issue of the thinkscr t hinkscr ipt for Leavitt’s convolution convolution Technical Analysis of indicator? Thank Tha nk you very much for your time.— STOCKS & COMMODITIES, “Leavitt Convolution.” I then logged David in to the S&C archives at Traders.com and read all al l of his previously published Author Jay Leavitt replies: articles in S&C. I just went into the thinkorswim platI am a user of thinkorswim and I see form and perused the list of studies that this is one of the trading platforms there, and I was able to fnd the Leavitt ca se, here that Leavitt uses. The thinkorswim thi nkorswim plat- convolution in the list. In any case, form has a very nice Hull moving average is the code:

plot LeavittConvolution = LeavittProjec LeavittProjec tion (LeavittProjection (price, n), intLength); } def price = Close; input length = 9; def intLength = Floor(Sqrt(length)); plot LeavittConvolution = LeavittProjection (LeavittProjection (price, length), intLength); LeavittConvolution.AssignValueColor(if LeavittConvolution > Leavit tConvolution [1] then C olor.GRE olor.GREEN EN else Color.RED) Color.RED);;

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TRADING ON MOMENTUM

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Gaps Got Your Stops?

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Intraday Swing Trading Basics Does “intraday swing trading” sound like a contradiction in terms? Well, it may actually not be because it combines the best of both worlds. Find out how this approach can solve some of the trouble spots of both daytrading and swing trading and ultimately boost proft potential.

by Ken Calhoun

O

ne of the biggest risks active traders str uggle with is holdholding positions overnight that gap against them, causing expensivee stop-losses. Classic daytrading expensiv daytra ding can also be challenging, because of the speed and accuracy needed to capitalize on early breakouts that move just $0.30–$0.80 during the opening hour. There is a hybrid trading approach that involves intraday swing trading, in which you enter your position during t he rst hour of the market open, then close the position at the end of the day. The main benet to this technique is much higher prot potential compared to clasclas sic daytrading, because when stocks run

up all day long you can gain as a s much as $1 to $5 per share in a single trade.

ENTER EARLY, EXIT LATE The best chart pattern to use this technique with is minor gap continuations, as seen in the chart of Canopy Growth Corp. (CGC) in Figure 1. Minor gaps are those in which the opening price gaps up less than 10%, for example, $3 or less for a $30 stock. I use buy stoplimit orders to enter all a ll of my positions. In this example, that would be a buy-stop $31.50 limit $32. I have found that my biggest error i n using this approach has been tightening up traili ng stops on winners and exiting my trades too soon. If you are a veteran daytrader, you may also experience thi s, because early prot-taking is a way of life. If I’m I’m up $0.80 per share on a trade t rade I just entered 10 minutes ago, for example example,, I usually tighten up my stop to lock in a prot. However, the solution that has worked best for me is to scale out, so I may exit half my winning trade with a tight stop at the rst sign of a pullback, but let the remaining half hal f of the position

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stay active until r ight before the closing bell, at which time I close the trade.

STEP-BY-STEP ACTION PLAN Here’s how you can start using this strategy. Scanning: Find a stock with a small gap up of less than 10%, as seen in

















Weeklys To To The Rescue

The 21st-Century Covered Call Are you tired of writing writi ng covered calls only to see your stock st ock get called away as it heads into the stratosphere? Here is a strategy that professional traders use to kill two birds with one option.

had unlimited unlim ited downside risk. If the stock closed lower lower than the naked leg stri ke price but above your cost for the underlying stock, you would have kept the premium, which lowered your averagee cost for the stock. averag The problem with this strategy was that when the stock

































OPTIONS

answer is a resounding yes. Over the years, this st rategy has evolved evo lved and allows traders and a nd investors a much better chance to make money. No approach offers more opportunity than what I call cal l the “21 “21st-century st-century covered call.” cal l.” Let’s Let’s look at how this strategy works. INITIATING THE 21ST-CENTURY COVERED -CALL STRATEGY

First, we must address the number-one problem of writing covered calls: losing the upside potential if the stock takes off. To To counter this situat ion, I sell a weekly call-credit call-cre dit spread instead of simply selling a call. To see how this strategy sets up, let’s let’s look at the t he option chain i n Figure 1 for Tesla Motor Co. (TSLA) when the stock closed at $320.87. With TSLA at $320 $320.87 .87,, the at-the-money (ATM) (ATM) call is the 320.0 and it is trading at approximately $11.60. We want to use the ATM strike as t he short call leg of the spread since it gives you the most premium. Under the old method of selling covered calls, you would buy the stock at $320.87 and sell the 320.0 call for $11.60. If the stock settled above $320, you would lose the stock at $320 but would keep the $11.60 credit $10.73 ($11.60 for a net gain of $10.73 ($1 1.60 credit cred it - $0.87 stock loss) lo ss).. Not a bad deal, but if i f the stock went on to $360, you would miss out on any proft past $10.73. Meanwhile, under the 21st-century covered-call strategy, you would buy the stock at $320.87, sell the 320.0 call at $11.60 and buy another call at a higher strike price with the same expiration date. You can buy any strike price you like but I recommend you buy one that is no more than $15.00 higher than t he ATM, which in this case cas e would be the 335.0 335.0 call (A (ATM TM +6). So you would buy buy the stock at $320 $320.87 .87 and initiate in itiate a 320.0– 335.0 call-credit spread by selling the 320.0 call for $11.60 and buying the 335.0 call for $5.70, resulting in a net credit of $5.90 ($11.60 - $5.70). If the stock settles above $325.90 ($320.00 + $5.90), let’s say $335.00, the call

return and you still own the stock. What about the downside? If Tesla’s stock were to close lower low er for the week, you would keep the $5.90 spread credit, which would limit your stock loss for the week. The good news is that no matter what happens, if you write the 21stcentury covered call for around a $5.90 credit 52 times a year, it would give you $306.80 ($5.90 × 52= $306.80) of downside protection, which is 95.6% of the purchase price of the stock ($320.87). HOW DOES

ALL THIS WORK IN REAL TIME?

Ideally, you want to do this covered-call strat egy with stocks Ideally, that have a good chance of trading higher over over the near term t erm and that also have liquid, weekly options. options. To select stocks that meet this criteria, criter ia, you can you can use a scanner similar to the one we offer at MarketEdge (www (www.marketedge.com, .marketedge.com, a website developed by Computrade Systems, Inc., Inc., which has been in i n existence as either a software application or website since 1992 1992). ). LOSS PROFIT / LOSS

SCENARIOS

FOR THE STRATEGY

There are six scenarios you can expect each week when employing employing this strategy: at, small smal l gain, rally ral ly,, big rally ral ly,, small smal l loss, and big loss. Using TSLA as an example, let’s check out the possible outcomes. Say you purchase 100 shares of TSLA at $320 and initiate the 320–335 call credit spread for $5.90. $5.90. For illustrative il lustrative purposes, the follow following ing assumes the option positions are closed on t he weekly expiration date and the stock position remains open. Each week there will be a realized gain or loss in your option account and an unrealized gain or loss in your stock account. Initial position: 100 100 shares (TSLA) ( TSLA) @ $320 $320 = $32,000 Options: 320–335 call credit spread @$5.90 = $590 credit

















1) Flat: The stock settles unchanged at $320 This is a no-brainer. no-bra iner. You You pocket the $590 from the call cred it spread. You have no change in your stock value. Continue the next week by initiati ng another 320.0–335.0 320.0–335.0 call credit c redit spread for a credit of around $5.90. $5.90. Total account a ccount value: $32,000 + $590 = $32,590 ($590 gain)

2) Small gain: The stock rises by about 1.5% to $325 You pocket the $590 from t he call credit spread on Monday, Monday, buy back the expiring in-the-money in-the-money (ITM) short call at $500 on Friday afternoon after noon (before expiration) expiration) for a realized gain gai n of $90 on the options, an unrealized gain of $500 on the stock. Continue the next week by initiating a 325.0–340.0 call credit spread for a credit cre dit of around $5.90. $5.90. Total account a ccount value: $32,500 + $590 - $500 = $32,590 ($590 gain)

3) Rally: The stock rallies by about 5% 5% ($15) to $335 You pocket the $590 from t he call credit spread on Monday, Monday, and buy back the expiring expiri ng in-the-money spread at $1,500 $1,500 on Friday afternoon afte rnoon (before expiration) for a realiz ed loss of $910 $910 on the options, an unrealized unrealiz ed gain of $1,500 $1,500 on the stock and you keep the stock.

You want to do this coveredcall strategy with stocks that have a good chance of trading higher over the near term and also have liquid, weekly options.

Continue the next week by initiating initiat ing another 33 335.0–350 5.0–350.0 .0 call credit c redit spread for a credit of around $5.90. $5.90. Total account value: $33,500 + $590 - $1,500 = $32,590 ($590 gain)

4) Big rally: The stock rallies rall ies by about 9% to $350 You pocket the $590 from t he call credit spread on Monday, Monday, and buy back the expiring i n-the-money spread at $1,500 $1,500 on Friday after noon (before expiration) for for a realized rea lized loss of $910 $910 on the options, an unrealized gai n of $3,000 $3,000 on the stock and Continued on page 33





































QUANTITATIVE ANALYSIS

Time As A Trading Signal

Does History Repeat Itself In The Markets? Seasonality or repeating patterns in nancial data can come in many shapes and sizes and can put the probabilities on your side. Or does general market m arket unpredictability unpredictabil ity ultimately u ltimately undermine that edge? Here are some ideas on looking for time-based patterns and an example of how to backtest ba cktest their reliability. reliability.

it possible to forecast market ma rket moves by using a “time “ti me factor”? Here, we’ll we’ll attempt to answer a nswer that question using monthly timeframes. For this study st udy,, we used the forex market and statistically analyzed historical monthly performances of some of the major currency pairs. We hypothesized that the major currencies vs. the US dollar, which is usually a mean-reverting relationship, could indicate

Is

Translating it into nancial terms, ter ms, we can easily dededuce that Kairos represen represents ts market timing timi ng,, relating to those ex ante, unpredictable times when an operating alert pops up and signals you to open long or short positions positi ons due to technical reasons. That reason could be a breakout of a resistance; reaching an a n overbought or oversold condition on a particular oscillator; the completion of a particular pattern; or so on. Kronos, on the other hand, represents the cyclical nature of events that regularly happen in nancial markets. Market timing (Kairos) is one of the pillars of technical analysis, while Kronos has not yet been deeply detected. The question could be: Do we need to wait for a technical “event” (such as the break of resistance/support, the cross of a moving average, or



















If the retur ns were mainly negative for for a given month, it was dened as a “bear“bearish” month. month. The entry point of the “trade” “ trade” was the open price of the rst t rading day of the month and the exit point was the closing price of the last trading day of the same month. 2. Out-of-sample Out-of-sample analysis. We then used the subsequent four-y fou r-year ear period p eriod (2014–2017) (2014–2017) to test the same signals. Using the same denitionss of bullish/bearish denition bullish/bear ish months as in the earlier i n-sample analysis, we we opened long trades in the months that were previously ousl y dened as bullish and short trades t rades in the months that were previously dened as bearish. bear ish. Near-zero-ret Near-zero-ret urn months weren’t weren’t included in this second step, as they were considered trendless.

Year

Jan

Feb

Mar

Apr

2.37% % 1998 -1.86% 0.93% -1.12% 2.37

May

Jun

-2.7 -2 .78% 8%

-3.2 -3 .25% 5%

-1.9 -1 .97% 7%

-1.8 -1 .85% 5%

-4.56% % 2000 -4.56

-0.6 -0 .68% 8%

-0.7 -0 .73% 3%

-4.7 -4 .70% 0% 2.33 2.33% %

-1.08% 2001 -1.08%

-1.5 -1 .54% 4%

-5.0 -5 .02% 2% 1.25% -5.06% 0 .5 .5 3% 3%

1999

-1.5 -1 .58% 8%

2.25 2. 25% % -2.6 -2.69% 9%

0 .2 .2 9% 9%

3 .3 .3 6% 6%

3 .6 .6 9% 9%

.6 8% 8% 2003 2 .6

1 .3 .3 1% 1%

2 .4 .4 3% 3%

5 .4 .4 5% 5% -1.6 -1.64% 4%

-2.63% -2. 63% 1.82% -0.05 -0.05% %

-1.91% 1% 2005 -3.81% 1.31% -1.9

-0.7 -0 .75% 5%

-4.3 -4 .32% 2%

.5 7% 7% 2006 2.62% -1.77% 1 .5

4 .2 .2 5% 5%

1 .5 .5 0% 0% -0.17 -0.17% %

2007 -1.27% 1 .4 .4 9% 9%

2 .1 .1 9% 9% -1.45% 0.67 0.67% %

2008

1 .8 .8 8% 8%

-8.28% 2009 -8.28%

2 .1 .1 3% 3%

3 .8 .8 1% 1% -1.08 -1.08% %

Sep 4 .3 .3 6% 6%

3 .1 .1 6% 6%

-4.1 -4 .12% 2%

-2.5 -2 .51% 1%

-1.7 -1 .72% 2%

Nov

Dec

-4.39% -4. 39% 0.05% 7.94 7. 94% %

-1.1 -1 .16% 6%

-0.5 -0 .51% 1%

-0.7 -0 .70% 0%

0 .4 .4 4% 4%

0 .3 .3 2% 2%

5 .4 .4 7% 7%

-2.1 -2 .18% 8% 6.00% -0.51% 3.63 3.63% %

4.70 4. 70% %

4 .1 .1 4% 4% -0.1 -0.11% 1%

-1.38% -1. 38% 1. 1. 15 15 %

0 .4 .4 3% 3% 2 .0 .0 4% 4%

2 .8 .8 8% 8%

1.78 1. 78% % -2.2 -2.25% 5%

-0.3 -0 .35% 5%

-1.6 -1 .60% 0% 0.41%

-0.20% -0. 20% 0.27% -1.05% 0.66 0.66% %

3.72 3. 72% % -0.32%

-1.7 -1 .76% 6% 0.26 0.26% %

1.01 1. 01% % -0.41% 4 .6 .6 8% 8%

-0.40% -0. 40% 1.25% -0.97 -0.97% %

-5.9 -5 .97% 7%

-4.1 -4 .12% 2%

-0.61% -0. 61% 5.00% -0.16% 7.05% -0.71% 1. 1.6 0% 0%

0 .4 .4 4% 4%

2 .1 .1 1% 1%

1 .0 .0 2% 2% -0.42%

-9.7 -9 .75% 5%

-0.5 -0 .55% 5% 10.12%

0 .5 .5 3% 3%

1 .8 .8 3% 3% -4.54%

-0.8 -0 .84% 4%

-1.6 -1 .60% 0%

62 % 2011 2 . 62

0 .8 .8 2% 2%

2 .5 .5 5% 5%

4 .5 .5 9% 9% -2.90% 0.73% -0.72% 0.10% -6.85% 3.85% -2.97 -2.97% %

1 .0 .0 8% 8%

1 .8 .8 4% 4%

0 .1 .1 2% 2% -0.90 -0.90% %

-3.85% % 2013 2.94% -3.85 -1.06% Avg -1.06% SHORT

-6.60% -6. 60% 2.44% -2.92% 2. 2.2 4% 4%

-1.82% -1. 82% 2.79% -1.28% 0.12 0.12% %

2 .0 .0 6% 6%

1 .5 .5 7% 7%

-1.6 -1 .69% 9%

2012

-0.5 -0 .54% 4% 6.65% -2.92% 7.53 7.53% %

3 .6 .6 1% 1%

-3.2 -3 .21% 1%

2010

-7.6 -7 .69% 9%

Oct

0 .8 .8 6% 6% -2.15% 1.05% -3.9 -3 .96% 6% 2.77 2.77% %

6 .1 .1 1% 1% -1.46% 0. 0. 43 43 %

-1.69% % 2004 -0.57% 0.14% -1.69

0 .9 .9 2% 2%

Aug 1 .9 .9 0% 0%

-0.5 -0 .59% 9% 3.34% -1.29% 1.08% -1.43 -1.43% %

1.2 1% 1% 2002 -3.39% 1. 0 .2 .2 5% 5%

Jul

0.07 0. 07% % -0.38% 1. 1. 05 05 %

2.27 2. 27% % -7.03% 3.09% -3.65% -3. 65%

2 .2 .2 3% 3%

0 .8 .8 6% 6%

0 .2 .2 2% 2%

1 .5 .5 1% 1%

2.21 2. 21% % -0.62% 2 .2 .2 4% 4%

0 .4 .4 1% 1%

0 .0 .0 5% 5%

1 .1 .1 4% 4%

-0.20% -0. 20% 0.03 0.03% %

0.60 0. 60% % -0.59% 0.52 0.52% %

0.40 0. 40% % -0.31% 1.04% -0.18 -0.18% %

-0.13% -0. 13% 1.74%

SHORT SH

LONG

LONG

SHORT SH

SHORT

LONG

SHORT

LONG

SHORT

LONG

FIGURE 1: AVERAGE MONTHLY RETURNS OF EUR/U SD EXCHANGE RATES, 1998–2013

N.

Note that whenever more than one month in a row presented the same t rend (bullish or bearish) bear ish),, the trade tra de wasn’t wasn’t closed and immediately reopened, but rather kept in place until a month of the opposite sign occurred. Our aim with this th is two-step analysis analysis was to verify the earlier long-term (15-year (15-year)) results in i n a shorter short er (four-y (four-year) ear) time period and a nd test whether the pattern patter n holds up—indicating up—indicating that history does sometimes tend to repeat repeat—or —or whether the markets are just too

1 2 3

Date

Trade

En.Price

Ex.Price

Jan 2014 Ja

Short

1.374

1.349

Feb Fe

Short

1.349

1.380

Mar

-

1.379

1.377

% Chg

Profit

-1.88%

258

2.30%

-310

-52

-0.11%

0

-52

0.72%

99

47

-1.71%

237

284 342

Cum. Profit 258

4

Apr

Long

1.377

1.387

5

May

Short

1.387

1.363

6

Jun

Long

1.363

1.369

0.43%

58

7

Jul

Long

1.369

1.339

-2.21%

-303

39

8

Aug

Short

1.339

1.313

-1.93%

258

297

9

Sep

Long

1.314

1.263

-3.85%

-506

10

Oct

Shor t

1.263

1.252

-0.84%

106

S

-209

-103



















A T T E N D T H E U LT LT I M A T E E D U C A T I O N A L E V E N T F O R A C T I V E

N E W YO R K March 10–12, 2019 | New York Hilton Midtown

TRADER S



















April, June, July, July, September, and December Decemb er can be considered bullish, bull ish, while January, February, March, May, May, August, and November are beari bearish. sh. October has a near-zero average return, so it’ it’ss considered trendless and wasn wasn’t ’t included in the out-of-sample out-of -sample test. With the benet of historical data series analysis, we adopted the same month-based long and short strategy st rategy for the subsequent 2014–201 2014–2017 7 period, going long (or holding long) in bull ish months and short in bearish ones. The table in Figure 5 shows all the t he trades (32 total trades— tra des—16 16 long and 16 16 short trades) and the chart i n Figure 6 shows the equity li ne for the strat egy (2,474 (2,474 pips earned ear ned on the t he whole). whole).

Year

Jan

Feb

Mar

0.91% % 1998 -0.85% 0.91

Apr

1.46 1. 46% % -0.06% -0.06%

May

Jun

Jul

Aug

-2.80% -2. 80% 1.37%

-0.4 -0 .43% 3%

-2.11% -2. 11% 0.77% -2.51% -2.51%

-3.43% -3. 43% 1.11% -1.40% -1.40%

-2.1 -2 .12% 2% 0.87% -0.99% -0.99%

0. 35 35 % 2002 -2.98% 0.

0 .6 .6 7% 7%

-3.16% -3. 16% 1.81% -1.79% -1.79%

-1.57% -1. 57% 4.63%

2 .0 .0 3% 3%

1 .5 .5 0% 0% -1.24% -1.24%

-2.09% -2. 09% 2.23%

1.99 1. 99% % -0.86% 1.39% -0.40% -0.40%

-0.42% -0. 42% 3.43%

-0.04% -0. 04% 0. 0. 64 64 %

2 .2 .2 0% 0% -0.20% 5.32 5.32% %

0.4 6% 6% 2003 2.32% -4.29% 0.

1 .1 .1 1% 1%

-2.14% -2. 14% 5. 5.1 9% 9%

2 .1 .1 1% 1%

1 .5 .5 6% 6%

2.60% 2004 2.60%

-3.57% -3. 57% 3.23% -0.73% 0.03% -1.05% 0. 0.5 1% 1%

1 .4 .4 2% 2%

3 .8 .8 1% 1%

0 .5 .5 1% 1%

-1.8 -1 .84% 4% 2.73% -1.98% 0.35% -2.20% -2.20%

-0.36% -0. 36%

2.38 2. 38% % -1.49% -1.49%

2 .4 .4 2% 2%

Dec

-1.5 -1 .56% 6% 2.77% -1.04% 2.72% -0.26% -0.26%

-2.77% -2. 77% 0.77% -0.09 -0.09% % -1.2 -1 .24% 4%

Nov

-1.74% -1. 74% 0.39%

-1.32% 2000 -1.32% -1.9 -1 .90% 0%

Oct

1.13 1. 13% % -1.47% -1.47%

-0.80% 1999 -0.80% 2001

Sep

-2.45% -2. 45% 2.05% -1.94% 2.91 2.91% %

2005 -1.83% 1.92% -1.56% 1.05% -4.67 -4.67% % -1.38% 2006 3.13% -1.38%

-0.96% -0. 96% 5.12 5.12% %

0.22% % 2007 0.31% -0.07% 0.22

1 .6 .6 5% 5% -2.76% -2.76% -1.4 -1 .49% 9%

2.64 2. 64% % -1.19% 1.12 1.12% %

1.59 1. 59% % -0.99% 1.48 1.48% %

0.14% 2008 0.14%

0.07 0. 07% % -0.11% 0.12% -0.19% 0.77% -0.40 -0.40% %

-0.78% 2009 -0.78%

-0.82% -0. 82% 0. 0. 37 37 %

3 .2 .2 6% 6%

-1.24% 2010 -1.24%

-4.51% -4. 51% 0.17 0.17% %

0.59 0. 59% % -4.65% 2.80 2.80% %

2.98% 2011 2.98%

1.51 1. 51% % -1.41% 4.24% -1.24% -1.24%

.6 1% 1% 2012 1 .6

0 .9 .9 8% 8%

-2.45% 2013 -2.45%

-4.38% -4. 38% 0.30 0.30% %

Avg

0 .5 .5 8% 8%

9 .4 .4 5% 5%

1.93 1. 93% % -1.64% 1.77 1.77% %

1.07 1. 07% % -0.70% 1.48 1.48% %

1 .7 .7 1% 1%

-8.2 -8 .20% 0%

1 .5 .5 4% 4% -2.58% -2.58%

1 .5 .5 1% 1% -5.07% 1. 1.9 3% 3%

0 .1 .1 0% 0%

1 .2 .2 1% 1%

2.26 2. 26% % -2.14% -2.14%

-0.0 -0 .09% 9% 1.98 1.98% %

-5.0 -5 .01% 1% -1.60% -1. 60%

1 .8 .8 5% 5%

0.51 0. 51% % -0.66% 0.81 0.81% %

SHORT

SHORT SH

SHORT SH

LONG

SHORT

-0.99% -0. 99%

0 .0 .0 1% 1% -0.73% 1.39%

4.34 4. 34% % -0.89% 2.05 2.05% %

-0.1 -0 .12% 2% 1.11% -0.54% 0.71 0.71% % LONG

2.04 2. 04% % -3.20% 0.30%

-4.18% -4. 18% 3.75% -2.39% -2.39%

-0.8 -0 .84% 4%

SHORT

-9.7 -9 .77% 7%

-3.39% -3. 39%

-1.90% -1. 90% 2.92% -0.09% -0.09%

-0.0 -0 .07% 7%

LONG

3.05 3. 05% % -0.36%

1.61 1. 61% % -1.12% -1.12% -4.5 -4 .57% 7%

4.97 4. 97% % -2.35% 2.41 2.41% %

-2.40% -2. 40% 2.29% -1.20% -1.20% -0.0 -0 .01% 1%

-1.6 -1 .67% 7%

3 .5 .5 4% 4%

1.20 1. 20% %

0.01 0. 01% % -0.78% 0.46%

LONG

SHORT

LONG

FIGURE 4 AVERAGE MONTHLY RETURNS OF GBP/USD EXCHANGE RATES, 1998–2013

USD/CAD

The third major we examined was the exchange rate between the US dollar and the loonie, that is, the Canadian dollar (usually abbreviated as Can$ or C$ to distinguish it from the US dollar). The table in Figure 7 shows all monthly returns of the exchangee rate from 1998 to 2013. exchang 2013. As usual, the last row of the table shows the average average returns retur ns for each month. On a historica l basis, January, June, July, August, October, and November are bullish months, while whi le Februar y, March, April, Apr il, May, May, September,

N.

Date

Trade

En.Price

Ex.Price

Jan 2014 Ja

Short

1.656

1.643

Feb Fe

Short

1.644

1.674

3

Mar

Short

1.675

1.666

4

Apr

Long

1.666

1.687

5

May

Short

1.687

1.675

6

Jun

Long

1.676

1.710

Jul Ju

Long

1.711

1.688

8

Aug

Short

1.689

9

Sep

Long

1.659

1 2

7

% Chg

Profit

-0.74%

123

Cum. Profit 123

1.82%

-299

-176

-0.50%

83

-93

1.27%

211

118

-0.73%

123

241

2.05%

344

585

-1.30% -1

-222

363

1.660

-1.71%

288

651

1.621

-2.30% -2

-381

270

0

270

329

599

10

Oct

-

1.621

1.600

-1.34%

11

Nov

Short

1 598

1 565

-2.06%





















Year

For each financial instrument, each month of the year has a particular bullish or bearish “personality” “personal ity” that lasts over time.

Jan

Feb

Mar

Apr

-2.23% % 1998 1.66% -2.23

-0.15% -0. 15% 0. 0. 86 86 %

-1.37% % 1999 -1.37

-0.1 -0 .18% 8%

-0.0 -0 .09% 9%

2001

0 .2 .2 1% 1%

2 .6 .6 0% 0%

2003

-3.2 -3 .28% 8%

-2.4 -2 .41% 1%

2 .5 .5 1% 1% -2.6 -2.63% 3% -1.0 -1 .05% 5%

Jun

Jul

0 .7 .7 1% 1%

3 .1 .1 1% 1%

Aug

Sep

Oct

Nov

3 .5 .5 0% 0% -2.28% 0.78% -0.65 -0.65% %

-3.3 -3 .32% 2% 1.24% -0.75% 2.99% -0.93 -0.93% %

2.19% % 2000 -0.17% 0.20% -0.11% 2.19 -0.56% 6% 2002 -0.44% 1.18% -0.5

May 1 .8 .8 4% 4%

-1.70% -1. 70% 0.31 0.31% %

0.22 0. 22% % -1.63%

1.18 1. 18% % -0.90% 0.51% -0.99% 1 .9 .9 7% 7%

1 .3 .3 0% 0%

1 .0 .0 3% 3% -1.53% 1.08%

1 .1 .1 4% 4%

1 .8 .8 6% 6%

0 .8 .8 2% 2% -2.38%

-0.5 -0 .52% 2%

-1.4 -1 .42% 2% 1 .2 .2 5% 5%

-1.6 -1 .66% 6%

-2.5 -2 .56% 6%

-1.3 -1 .30% 0% 4.39% -1.60% 1.91% -1.76% 0.82 0.82% %

0.51 0. 51% %

-2.5 -2 .50% 0%

-4.5 -4 .59% 9%

-1.6 -1 .65% 5% 4.42% -1.49 -1.49% %

-2.5 -2 .56% 6%

-2.1 -2 .17% 7%

-1.5 -1 .53% 3%

-0.0 -0 .07% 7%

-3.5 -3 .53% 3%

-2.5 -2 .50% 0% 1.38%

-0.11% % 2004 2.26% -0.11

-1.76% -1. 76% 4.83% -0.8 -0.87% 7%

-2.1 -2 .14% 4%

-0.1 -0 .14% 4%

-0.9 -0 .96% 6%

-3.8 -3 .89% 9%

2005 3.31% -0.41 -0.41% %

-2.02% -2. 02% 4.00% -0.4 -0.40% 0%

-2.3 -2 .35% 5%

-0.1 -0 .17% 7%

-2.8 -2 .89% 9%

-1.7 -1 .73% 3% 1.33% -1.26 -1.26% %

-2.28% 2006 -2.28%

-0.25% -0. 25% 2.77% -4.38 -4.38% %

-0.59% 9% 2007 0.96% -0.5

-1.3 -1 .33% 3%

-3.7 -3 .76% 6%

-1.70% % 2008 0.39% -1.52% 3.94% -1.70 2009

0.56 0. 56% %

3.81 3. 81% % -1.18 -1.18% %

-5.3 -5 .36% 6%

-1.76% % 2010 1.65% -1.76

-3.54% -3. 54% 0 .2 .2 7% 7%

-2.95% 5% 2011 0.57% -2.9

-0.1 -0 .11% 1%

-1.85% 2012 -1.85% 2013

0.47 0. 47% %

-1.44% -1. 44% 1.40 1.40% % -3.7 -3 .70% 0%

1.31 1. 31% % -2.48% 1 .3 .3 0% 0%

-0.3 -0 .32% 2% 0.12% -1.0 -1.01% 1%

-1.46% -1. 46% 2 .6 .6 2% 2%

0 .3 .3 2% 2%

3 .8 .8 4% 4%

-6.0 -6 .04% 4% 0 .2 .2 5% 5%

0 .4 .4 5% 5%

1 .6 .6 2% 2%

2 .6 .6 8% 8%

1 .8 .8 7% 7% -3.22% 3.54% -3.42 -3.42% %

-2.6 -2 .63% 3% 2.47% -0.54 -0.54% % -1.00% -1. 00% 2.99 2.99% %

1 3. 3.8 8% 8%

2 .2 .2 2% 2%

2 .2 .2 8% 8% -1.25% -0.28% -0. 28%

-0.97% -0. 97% 0.65% -2.77%

-0.82% -0. 82% 2.42 2.42% %

7.43 7. 43% % -4.67% 1.68 1.68% %

0.36 0. 36% %

-1.3 -1 .35% 5%

-0.2 -0 .25% 5% 1.65% -0.52 -0.52% %

-0.15% -0. 15%

-1.6 -1 .67% 7%

1.47 1. 47% % -2.31% 2.50% -2.14% 1 .1 .1 6% 6%

1 .7 .7 6% 6%

0 .1 .1 0% 0%

-0.15% 5% Avg 0.17% -0.1

-0.2 -0 .20% 0%

-1.1 -1 .12% 2%

-0.4 -0 .44% 4% 0 .1 .1 1% 1%

0 .1 .1 9% 9%

0 .2 .2 7% 7% -0.72% 0.32 0.32% %

0.32 0. 32% % -0.22%

L ON ONG

SH OR ORT

SHO RT RT

SH OR ORT

L ON ONG

L ON ONG

L ON ON G

SHO RT RT

L ON ONG

SHO RT RT

L ON ONG

FIGURE 7: AVERAGE MONTHLY RETURNS OF USD/CAD EXCHANGE RATES, 1998–2013

harnessing harnessi ng time in monthly windows has proved

-0.33% -0. 33%

-5.1 -5 .10% 0% 5.90% -0.08%

-8.5 -8 .57% 7% 6.64% -7.30% 1.44% -2.20% 1.38% -2.59 -2.59% %

-1.27% -1. 27% 0.84% -1.13% 4.61% -1.5 -1.58% 8% 3.36 3. 36% % -1.29 -1.29% %

Dec -0.25% -0. 25%

S HO HO RT RT





























































TRADING TECHNIQUES

anticipate and spot them and take appropriate action when they are formed. To illustrate, I have come up with a few examples on different markets and various timeframes so that you too can potentially spot these patterns. SELLING

W E I V G N

INTO SUPPORT

False breaks can happen on any timeframe. Generally speaking, the higher the timeframe, timefram e, the better the quality of the setup. But even on the one-minute chart, such as in this example of the Nasdaq 100 in Figure 1, the markets can form false break reversal





















WHAT’S

THE IDEAL ENTRY POINT?

False breaks can be traded many different ways and on different timeframes. In the daily chart of the S&P 500 futures in Figure 2, I have highlighted at least three different areas to buy around, after the false break took place. Here, the S&P spiked below the old low at 180 1805 5 but the sellers couldn’t hold their ground for too long. To some degree, the fakeout here could have been anticipated given the magnitude of the prior drop and as the relative strength index (RSI), which is a popular momentum indicator, was in a state of positive divergence diverge nce already al ready as the index retested that t hat low. low. That is, t he RSI was making a higher low as the underlying S&P index tried to break its old low, clearly indicating that the selling momentum was waning. As the false break could have been anticipated, intraday traders could c ould have potentially bought near t he low, low, based on price action on a smaller timeframe chart such as the hourly

The beauty of the false break setup is that sometimes s ometimes price goes significantly in the opposite direction, hence the saying “from false moves come fast moves in the opposite direction.”

closes lower lower than the opening price. pr ice. It clearly shows shows that the t he buying pressure has ended abruptly. These types of candlesticks are most effective when they occur at the top of trends, around old resistances or prior























Notice of Class Action Settlement If you transacted in Euribor Products1 between June 1, 2005 and a nd March 31, 2011, inclusive (“Class Period”), then your rights will be affected and you may be entitled to a benefit. The purpose of this Notice is to inform you of your rights in connection with the proposed settlement with Settling Defendants Citigroup Inc. and Citibank, N.A. (collectively “Citi”) and JPMorgan Chase & Co. and JPMorgan Chase Bank, N.A. (collectively, “JPMorgan”) in the action titled Sullivan, et al. v. ., 13-cv-2811 (PKC) (S.D.N.Y.). The settlement Barclays plc, et al .,

Defendants make false Euribor submissions on their behalf to benefit their Euribor Products positions. Plaintiffs further allege that Defendants Defendants continuously continuously conspired to fix the prices of Euribor Products in the over-the-counter market to financially benefit their own Euribor Products positions In addition to coordinat coordinating ing Euribor submission and























(continued from previous page)

Notice of Class Action Settlement If you transacted in Euribor Products1 between June 1, 2005 and March 31, 2011, inclusive (“Class Period”), then your rights will be affected and you may be entitled to a benefit.

The fakeout, if traded correctly, could be a very lucrative setup, requiring very few indicators but a lot of common sense and a ton























You would rather make $100 from a 10-point move, risking $10 per point, rather than from a 100-point move, risking $1 per point. In both cases, the nominal and























Algo Q&A ALGORITHMIC TRADING Have a question quest ion about system or algo trading? Kevin J. Davey has ha s over 25 years of system trading experience. Davey is a full-time full-time trader, and he also teaches and an d consults via his Strategy Factory online onlin e workshop (http://kjtradingsystems.co (http://kjtradingsystems.com) m).. H e is the author of several bestselling trading books, including Building Winning Algorithmic q uestions or topic sugTrading Systems and Introdu Introduction ction To Algo Trading. Send your questions gestions to Kevin Davey at [email protected]. S elected elected questions will

















































































































































































































































































































































































































































































































































Algo Q&A DAVEY Continued from page 25

As you can see, I spend the bul k of my time developing strategies. This is also the hardest task, since many potential strategies get thrown away before an

GARNER Continued from page 41

volatility the risk might prove to be much less or moderately more). Those accustomed to buying options or trading futures might look at this risk and reward prole as unattractive, but that assumption is overlooking the primary benet of option selling; options options are eroding assets that generally expire worthless. Thus, risking more than the expected payout makes sense if it is expected that the winners will conside considerably rably

KAEPPEL Continued from page 47

As you can see in Figure 4, the trader can make money if crude oil rallies sharply or falls sharply but will suffer time decay if USO remains relatively unchanged. Still, the worst-case scenario for this position is an open prot of +$318. The benefits of adjusting Everything in trading is a tradeoff. This is especially true tr ue when adjusting adjusting an option position. In most cases, you give up something (in these examples, primarily a certa in amount of prot potential) in order to get something (in these examples, the elimination elim ination of this risk r isk of loss). loss). Often

acceptable one is found. So this task is frequently frustrating, which may be one reason people do not spend enough time on it. Meanwhile, I still spend signicant time on the other t asks, which helps keep keep every trading day interesti ng. While every algo trader’s time allocaal loca-

tion will be different, hopefully you now have an idea of what to expect in the life of an algo trader. I’m sure you’d agree it is much different than for discretionary trading.

outnumber the losers. I should point out that because the protection expires prior to the short option, it will eventually be necessary for the trader to either purchase fresh insurance for the remainder remai nder of the trade, exit the short option upon expiration of the protective put, or face theoretically unlimited risk beyond expiration of the February option. In other words, unlike vertical credit spreads, diagonal spreads require moderately more attention and ongoing management. The strategy of purchasing catastroph-

ic insurance outlined here should not be confused with a strategy that offers absolutely limited risk, nor should it be assumed that normal ebb and flow of market pricing won’t impact this trade. What I’ve outlined here is simply a way for option sellers to continue with premium-collection efforts without exposing themselves themselves to the tail tai l risk and account blowups that can occur on rare occasions.















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