Barclays Special Report Market Neutral Variance Swap VIX Futures Strategies

Equity Research 28 April 2014

Special Report

Market Neutral Variance Swap & VIX Futures Strategies

DERIVATIVES U.S. Equity Derivatives Strategy U.S. Equity Derivatives Strategy

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It is perhaps not well appreciated that short variance swap (SVS) strategies which efficiently capture the volatility risk premium (VRP) have a significant market exposure. Removing this market exposure requires an additional position in the underlying index. In this note, we present several methods to calculate this “variance swap delta” and thus construct market-neutral SVS strategies. In general, we find that the Sharpe ratios of these strategies do not materially change, attesting to the fact that the VRP cannot be fully attributed to the Equity Risk Premium (ERP). We first use the well-known replication strategy for variance swaps to derive an explicit formula for the variance swap delta. We show that a non-zero value requires the presence of a volatility smile. Our first method to calculate the variance swap delta is to simply use the Black-Scholes formula for the delta of the replicating option strip. This is equivalent to the “sticky strike” model, where strike volatilities are assumed to not change. This approach does not capture the fact that strike volatilities themselves react and hence does not fully remove the market exposure. We next show that the variance swap delta can also be calculated by simply combining the sticky strike assumption with the approximation formula for the variance swap strike as a function of smile curve parameters. The advantage of this approach is that we can now incorporate the empirical dynamics of the strike volatilities by using the “skew stickiness ratio” (SSR), which can be calculated by regressing changes in at-the-money (ATM) volatility versus the skew-adjusted index returns. Historically, the SSR is ~1.5 as opposed to the value of 1 predicted by the sticky strike model. A simple way to incorporate this empirical fact is to simply scale up our calculated sticky-strike variance swap delta by the empirical SSR. We show that the empirical market beta of the resulting hedged SVS strategy is now almost zero. In the final section, we use the above methodology to calculate the delta of VIX futures and construct market neutral-short VIX futures strategies. The results are similar in that the Sharpe ratios are not materially affected by removing the market beta.

Barclays Capital Inc. and/or one of its affiliates does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. PLEASE SEE ANALYST CERTIFICATION(S) AND IMPORTANT DISCLOSURES BEGINNING ON PAGE 19.

Maneesh S. Deshpande

1.212.526.2953 [email protected] BCI, New York Ashish Goyal 1.212.526.2771 [email protected] BCI, New York Arnab Sen 1.212.526.5429 [email protected] BCI, New York

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Barclays | Special Report

Introduction It is perhaps not well appreciated that short variance swap (SVS) strategies that efficiently capture the volatility risk premium have a significant market exposure. This beta stems from the fact that realized volatility itself is negatively correlated with market returns. We estimate that nearly 25% of the return of a SVS strategy can be attributed to its beta exposure. Removing this market exposure requires an additional position in the underlying index, which we define to be the “delta” of the variance swap. In this note, we present several methods to calculate this delta and thus construct market neutral SVS strategies. Note that this variance swap delta is quite distinct from the exposure required for replicating the variance swap. The well known replication strategy for variance swaps involves a static (i.e. non delta-hedged) position in a strip of options and a dynamic exposure to the underlying (“the replication delta”), which is completely model independent. In a pure Black-Scholes world, the delta of the option strip exactly cancels the replication delta and thus the variance swap delta is always zero. In the presence of a volatility smile, the variance swap delta is not zero. Our first method to calculate the variance swap delta is to simply use Black-Scholes formula for the option strip delta. This approach implicitly assumes a “sticky strike” model for the implied volatility surface where the strike volatilities are assumed to stay constant when the underlying moves, which of course is not true empirically. Indeed, we show that with this approach, although the market exposure of the SVS strategy decreases, it does not drop completely to zero. We next show that the option strip delta can also be calculated by simply combining the sticky strike assumption with the approximation formula for the variance swap strike as a function of smile curve parameters. The advantage of this approach is that we can now incorporate the empirical dynamics of the strike volatilities by using the “skew stickiness ratio” (SSR), which can be calculated by regressing changes in ATM volatility versus the skew adjusted index returns. Empirically, the SSR is ~1.5 as opposed to the value of 1 predicted by the sticky strike model. A simple way to incorporate this empirical fact is to simply scale up our calculated variance swap delta by the empirical SSR. We show that the empirical market beta of the resulting SVS strategy is now almost zero. In general, we find that the Sharpe ratio of this strategy does not materially change, attesting to the fact the VRP cannot be fully attributed t o the Equity Risk Premium (ERP). The results of this note also help in understanding the difference in performance of delta hedged straddles with that of a pure variance swap, especially during periods of strong market rallies. While the DH straddles suffer from more path dependency, they also have less positive market exposure, because of which they are likely to underperform un-hedged variance swaps during strong market rallies. In contrast, delta-hedged straddles perform much better during market downturns. In the final section, we use the above methodology to calculate the delta of VIX futures and construct market neutral short VIX futures strategies. The results are similar in that the Sharpe ratios are not materially affected by removing the market beta.












Variance Swap Strategies: Pure but not market neutral Variance swaps are a pure means to trade volatility since their payoff is simply the difference in the squares of implied and realized volatility. Thus the payoff for a variance swap with variance notional of $1 can be written as:

     



Where is the variance swap strike and is the realized volatility during the tenor of the variance swap. In contrast, a delta-hedged option strategy suffers from significant path dependence in the sense that paths with the same realized volatility can have significantly different payoffs. This feature has made short variance swap (SVS) strategies an attractive vehicle for investors to harvest the premium of option implied volatility versus subsequent realized volatility (the so called Volatility Risk Premium, or VRP). As shown in Figure 1, 1, long term performance of SVS strategies is quite attractive. FIGURE 1 Short variance swap strategies have outperformed equities…

FIGURE 2 …With attractive risk-adjusted returns

Cum. Excess Returns

Avg. Ret.

St d. Dev.

Sharpe Ratio

Drawdown

SPX ER

7 .2%

20. 1%

0. 36

-61%

SVS

6 .5%

5. 2%

1. 25

-24%

Strat egy

350 300 250 200 150 100 50 Jan-96

Jan-00

Jan-04

Jan-08

SP X

SVS

Jan-12

Source: Barclays Research, Bloomberg, OptionMetrics Note: Excess return for SPX calculated by subtracting Fed-fund rates from the daily returns of SPX total returns. The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Transaction costs are ignored.

Source: Barclays Research, OptionMetrics, Bloomberg Note: Excess return for SPX calculated by subtracting Fed-fund rates from the daily returns of SPX total returns. The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Transaction costs are ignored. Data from Jan 1996 to April 2014.

However, as can been seen visually from Figure 1, 1, the SVS strategy appears to be correlated with the underlying index. Quantitatively, the daily and monthly correlations between the two indices are 58% and 55%, respectively. Figure 3 shows 3 shows that this market dependence is quite non-linear. As expected, large negative index returns will naturally result in large draw-downs for the SVS strategy. However, it is noteworthy that the slope around the origin or the beta for small market moves is still non-zero. At first glance, this market dependence might appear to be at odds with the fact that the P&L of a variance swap is supposed to only depend on realized volatility and not the underlying index return. After all, isn’t the whole point of using variance swaps to mitigate












FIGURE 3 Short variance strategy has a non-linear market exposure…

FIGURE 4 …Driven by the strong asymmetric dependence of realized volatility on index returns SPX 1M RV

SVS 1M Ret 5% 0% -5% -10% -15% -20% -25% -25% -20% -15% -10% -5%

0%

5%

10% 15% 20%

SPX 1M Ret Source: Barclays Research, OptionMetrics, Bloomberg Note: Dashed lines denote the 1 std deviation band around the mean. The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Transaction costs are ignored. Data from Jan 1996 to April 2014.

100 90 80 70 60 50 40 30 20 10 0 -25% -20% -15% -10% -5%

0%

5%

10% 15% 20%

SPX 1M Ret Source: Barclays Research, OptionMetrics, Bloomberg Note: Dashed lines denote the 1 std deviation band around the mean

The resolution of this apparent contradiction is a bit subtle. The P&L of a variance swap is indeed only dependent on the realized volatility of the path and not its other details (including the total return). However, it is an empirical fact that realized volatility is higher when the market sells off (as shown in Figure 4). 4). Although the implied volatility (or the variance swap strike) does try its best to capture the distribution of realized volatility, it is after all a single number, and as a result the dependence of realized volatility on market returns means that some market exposure is unavoidable for a SVS strategy. Note that for an opportunistic investor who trades variance swaps to express a view on subsequent realized volatility, there is no contradiction. As long as their view of realized volatility is correct, the P&L of the variance swap will be as expected. However, and this is the crucial point, any forecast of realized volatility also has an imbedded implicit market return forecast. The above discussion implies that at least part of the VRP harvested using SVS strategies is simply a result of the fact that equities have rallied, or that an Equity Risk Premium (ERP) exists. To quantitatively assess this, we regress the SVS strategy versus SPX returns and look at the intercept (alpha). Figure 5 shows 5 shows the results for a SVS strategy where we sell 0.2 vega for $100 capital. Since the average return of the SVS over this time period was 0.51% per month, we see that 0.12% can be explained by market beta. Said differently, on average 2.5 vol points were made over this time period using variance swaps, but 0.6 volatility point can be attributed to the positive market return over this period.












FIGURE 5 About 25% of the returns of SVS can be attributed to market exposure Avg. SVS Monthly Ret.

Al pha

Beta t o SPX

Al pha t St at

Bet a tS tat

R^2

0.51%

0.3 9%

0. 18

2.0 5

2 .16

30. 2%

Source: Barclays Research Note: Monthly SVS returns are regressed against monthly SPX returns. T-stats adjusted for overlapping returns. The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. No transaction costs assumed. Data from Jan 1996 to April 2014.

Thus an investor who would like a market neutral SVS strategy would need to hold an additional short position in the underlying index, which we denote as the “variance swap delta.” The main goal of the rest of this note is to develop a methodology to calculate this variance swap delta. The simplest approach would be to simply use the beta obtained using the empirical regression above. This suggests that for the particular SVS strategy discussed above, one is required to hold a $18 short SPX position for every $100 capital in the strategy. Note that this delta is of course dependent on the leverage or the vega being sold (in this case 0.2 per $100 of capital). However, this approach is clearly too crude. Recall that the beta calculation is based on monthly returns (the returns over the entire life of the variance swap) and presumably one should ideally adjust the hedge as the variance swap approaches maturity. In addition, the beta is clearly based on long term average reactivity and does not use any forward looking information imbedded in option prices. In the next few sections we develop a methodology to infer the variance swap delta from option prices.

Understanding Variance Swap Delta Variance Swap Replication In order to understand the variance swap delta, it is first useful to briefly review the variance swap replication methodology. The key insight which emerged from a series of papers in the mid-1990s was that a long variance swap can be replicated by a static position in a portfolio of vanilla option contracts and a dynamic position in the underlying index.



Thus consider a long position in a variance swap with maturity initiated at time 0 with an initial strike of and a $1 variance notional on an underlying which evolves according to:

0

     



Where the volatility can be an arbitrary function of and also can be stochastic. However, we assume that there are no jumps possible. If we assume that a constant interest rate and continuous dividend yield , we can recast this in terms of the forward



  














(which occurs at time ), can be written as a sum of the accrued (known) and mark-tomarket (unknown) payoffs as:

  

          0,           



is the past realized variance and is the future (unknown) realized variance. is the remaining life of the variance swap. The crucial insight is that the future realized variance can be written as:



1   1      log  2 2     

  

is the value of the forward on the index expiring at time as of time (Thus ). The first term can be replicated by a dynamic position in the forward on the underlying index. The second term is simply a function of the final value of the index and this log payoff can be replicated using a series of calls and puts. If we assume that the boundary between puts and calls we use occurs at strike , it can be shown that:

 log   log           ,0     ,0 ,0

Hence the payoff can be written as:

     0  2 log    2    2                2     ,0     ,0 ,0    Note that the above equations at this stage do not involve any expectations and so the above replication is valid for an arbitrary path. A particularly powerful feature of this replication methodology is that it is model independent. The dynamic hedging required is obviously model independent and, given its static nature, so is the option position. We emphasize again that only the second term leads to a dynamic position in the underlying; the other terms are static exposures and do not need any rebalancing. We need to distinguish the “replication” delta, which is required to replicate the variance swap, from the variance swap delta that we are interested in. An investor seeking to invest in a SVS strategy is not interested in replication. The goal is to simply remove the market exposure of the variance swap. We next look at two alternative (but equivalent) ways of calculating the variance swap delta.

Variance swap delta by directly using the replicating portfolio Since the variance swap can be replicated by the above portfolio, the variance swap delta is simply the sum of the “replication delta,” the delta of the forward and the delta of the option strip. •

The first term in square brackets is independent of the final value of the underlying and













Barclays | Special Report number of contracts of the underlying index that needs to be held for a $1 variance  notional is with the term offsetting the interest rate cost.

 

•



The third term is a static position position in the forward which can be replicated with a short  position of contracts in the underlying. We need the since the stock will also

 



pay dividends. •

Finally, the fourth term is a static position position in vanilla options with weight of strike option.

  for a 

Adding the last three terms we get:

∆ 2        ∆   ∆ 

Where

∆ ∆ and

are the put and call deltas for each option.

Variance swap delta by calculating the derivative of expected P&L We next present an alternative more automatic approach. The idea is to calculate the riskneutral expected value of the mark to market P&L, and differentiate it with respect to as we would do for any derivative contract. Taking expectations for the expression for future realized volatility, we get:





1   1    log               2 2                 ,      0          0         2 log       2             

Where we introduce the variance strike, as of time for the variance swap expiring at time and we have used the following two identities:

Using , we can then finally write the risk-neutral expected value of the markto-market P&L as:











Barclays | Special Report model which properly captures the actual dynamics of the underlying. We address this in the next section.

Accuracy of the replicating portfolio: An empirical examination The above results depend on several assumptions: •

•

•

•

The derivation of the replication portfolio breaks down if the underlying has jumps, which SPX clearly does. The exact replication portfolio requires us to trade a continuum of strikes from zero to infinity. In reality we only have a limited number of discrete strikes. The derivation assumes that the realized volatility in the variance swap is calculated using continuous time. The typical variance swap contract calculates the realised volatility using daily moves. The “replication delta” is assumed to be rebalanced continuously, which is of course impractical.

Thus it is interesting to empirically check how well the replicating portfolio using available listed options is able to capture the actual payoff of the variance swap. Figure 6 shows 6 shows the result of precisely this exercise. To be specific, on each SPX option expiration, we construct the static replicating portfolio using all the available one month listed SPX options with nonzero bid price. The variance swap strike is also calculated using the same option strip using the standard VIX formula. At the close of every day over the next month we do the required model-independent rebalancing. The actual payoff of the variance swap is then the difference between the implied and realized variance calculated using the daily returns. The payoff of the replicating portfolio is the final value of the static option strip on expiration and the P&L due to the daily rebalancing. FIGURE 6 Historically,, variance swap payoff can be accurately replicated using the replicating Historically portfolio Monthly Returns of SVS SVS Strategy 4% 2% 0% -2%

Difference in Returns 0.5% 0.4% 0.3%












Approximations for the Variance Swap Delta In this section, we explicitly calculate the variance swap delta using a series of better approximations. We first verify that the variance swap delta in a Black Scholes world (no smile) is zero. In the presence of a smile, the simplest approximation is to apply the BlackScholes formula to calculate the deltas for each option. Although this “sticky strike delta” is non-zero it does not fully remove the market beta since it ignores the fact that strike volatilities themselves have market dependence. We next develop a methodology to account for strike volatility dynamics using the Skew Stickiness Ratio (SSR) approach we have used in past publications.

Variance Swap Delta in a Black-Scholes world As a first step we calculate the “variance swap delta” assuming that the index follows the ideal Black-Scholes dynamics. In this case it is simpler to start with:

1     log  2  It is simple to calculate the integral for a geometric distribution and we get:



 log     12   

Since this is independent of , the delta is zero. Thus in the Black-Scholes world, the replication delta is exactly opposite to the log-contract delta. This makes sense since in this world the realized volatility is explicitly constant. Thus if options are priced using a different volatility, the variance swap will capture the VRP independent of the index return. The real world is of course not that of the Black-Scholes type. The smile to a large extent reflects the option markets attempt to capture the non-normal dynamics of the underlying index. As a result in the presence of volatility smile, the log-contract delta will not be equal to the replicating delta and thus variance swap delta will be non-zero. Ideally, we should use a full stochastic volatility model capable of reproducing the volatility surface and then calculate the option strip delta using this model. Since that would be a non-trivial exercise, we next present a series of simple approximations which we believe are adequate for our purpose.

Variance Swap Delta in the presence of a smile: Sticky Strike Approach












FIGURE 7 Sticky Strike Delta is able to vary according to market conditions Sticky Strike Delta (in $) required to hedge SVS 5 0 -5 -10 -15 -20 -25 -30 -35 Jan-96

Jan-99

Jan-02

Jan-05

Jan-08

Jan-11

Jan-14

Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. See text for more details.

To remain faithful to the replication strategy, strictly speaking we should set up the option strip at trade initiation and simply calculate the delta of this portfolio. However, there are two disadvantages to this approach. First, as the underlying index moves, the initially out of the money (OTM) options will become in the money (ITM), and become relatively more illiquid. As a result, the deltas calculated using the listed prices are likely to be more noisy. One way to mitigate this is to calculate the deltas using the OTM options and convert those to ITM deltas using put call parity. A more serious problem is that the initial portfolio is limited to options with non-zero bid price. This means that if the underlying moves significantly, we might end up in a situation where we have very few OTM options. We could address this problem by holding a position in all the listed strikes irrespective of the bid price. An alternative and completely equivalent approach is to simply to reset the , every day. We emphasize that although is typically chosen to be as close to the forward as possible, the choice is completely arbitrary from a purely mathematical point of view. If we choose a different , the change in the option delta will be completely offset by a change in the static forward ( ) term.





 1/

In Figure 8, 8, we show the time series of un-hedged short 1M variance swap and short 1M












FIGURE 8 Hedged SVS using sticky strike delta has lower returns and also lower draw-downs draw-downs… … 350

FIGURE 9 …But the correlation of the hedged SVS with SPX is still mostly positive Rolling 6M Correlation to SPX 100%

300

80% 60%

250

40% 20%

200

0% -20%

150

-40% 100 Jan-96

Jan-00

Jan-04

Unhedged SVS

Jan-08

Jan-12

Hedged SVS

Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Hedged SVS here is using sticky strike delta for hedging.

-60% Jan-96

Jan-00

Jan-04

Unhedged SVS

Jan-08

Jan-12

Hedged SVS

Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Hedged SVS here is using sticky strike delta for hedging.

Approximation for the Sticky Strike Delta Since the variance swap delta in the sticky strike approach involves a summation over all the Black-Scholes deltas, it is hard to get any intuition of its properties. However, as we discuss next, we can produce a simple formula based on the approximation for the fair variance swap strike. This approach will also help us to go beyond the sticky-strike approximation. The key insight is that the above approach implicitly assumes that the implied volatilities follow a sticky-strike model where the strike volatilities are assumed to remain constant. As we have discussed in previous publication (Special Report: Understanding VVIX ) it is possible to write down simple approximations for the variance swap strike using simple parameterizations for the volatility smile curve. In particular, assume that the smile curve can be well approximated as a simple quadratic in the log-strike ( ). I.e.:

       Then it can be shown that the variance strike can be written as:

  log/













Barclays | Special Report This directly gives an estimate for the variance swap delta as a function of the curve parameters:

∆     2  3  1818   6  2

To judge the accuracy of this formula we start with a specific parameterization for the volatility surface using typical empirical values for SPX and then calculate the variance swap delta by directly pricing the strip of options and by using the above approximate formula. As shown in Figure 10 10 the above formula closely replicates the actual variance swap delta calculated using the actual option deltas. For simplicity we only show the delta calculated at trade initiation (one month to expiry). FIGURE 10 Delta from option strip is close to the delta calculated from approximate variance strike formula Delta (in $) required to hedge SVS 0 -5 -10 -15 -20











Barclays | Special Report Thus, in a world where the options follow a sticky strike model, the SSR (Skew Stickiness Ratio) would be equal to 1. In case strike volatilities themselves increase as the spot declines, the SSR would be greater than 1. It can be shown that for a local volatility model, the SSR is always 2. The situation for more general stochastic models is more complicated. In the absence of jumps for very small expirations, the SSR is still 2 but approaches 1 for very large expirations. Presence of jumps will decrease the SSR ratio. Intuitively, this is because part of the skew can now be attributed to the jumps. j umps. In Figure 11, 11, we show the empirical SSR for 1M, 2M and 3M SPX volatility using 2-year rolling window. We see several interesting trends: •

•

•

In general, the SSR does deviate significantly from 1 and is typically higher than 1. The SSR appears to have gone through some regime shifts. It used to be much closer to 1 prior to 2007 and appears to have reached a higher level post the 2007-08 crises. In general, there does not appear to be much of dependence on option maturity. Thus the SSR ratios calculated using 1M, 2M and 3M options appear to be quite close.

FIGURE 11 SSR is higher than 1 and appears to have increased after 2007 Rolling 2Y SSR 2.0 1.8 1.6











Barclays | Special Report transaction costs. We also include the performance of an ATM delta-hedged straddle as a point of comparison. FIGURE 12 While the hedging does reduce the overall returns of SVS, the hedged SVS still appears to be better than short-delta-he short-delta-hedged dged straddles 340 290 240 190 140 90 Jan-96

Jan-00 Unhedged SVS Hedged SVS (Rolling SSR)

Jan-04

Jan-08 Jan-12 Hedged SVS (SSR =1) Hedged SVS (SSR = 2.0)

Delta Hedged ATM Straddle Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital. Transaction costs are ignored.

FIGURE 13 The Sharpe ratio of hedged SVS is not significantly different from unhedged SVS,











Barclays | Special Report SVS with respect to monthly SPX returns. From Figure 14, 14, we also observe that this low correlation of the hedged SVS with SPX has been effective in different regimes and as such we do not see any biases in it. Figure 15 shows 15 shows that the average monthly returns of SVS are now insensitive to moderate monthly returns in SPX. •

15 also demonstrates that the exposure to large Impact on draw-downs: Figure 15 moves remains significant. The draw-downs of hedged SVS are not significantly lower than the draw-downs of un-hedged SVS. This is because of the strong convexity SVS has relative to the SPX returns, and as such hedging can reduce the decline in returns only when SPX declines are moderate (5%-10% per month).

•

Alpha of hedged SVS : We see that even the market neutral variance swap has high Sharpe ratio and thus, it has significant positive alpha. Thus, the VRP appears to be a robust phenomenon and does not completely disappear after the market beta is removed.

•

Implications of over-hedging: An over-hedging SVS strategy actually results in a negative correlation of SVS with SPX. This reduces the Sharpe ratio of the strategy as the standard deviation starts to increase and average returns decline because of drift in SPX.

•

Short ATM delta hedged straddles correlation to SPX : Delta-hedged ATM straddles using Black-Scholes implied volatility have a similar correlation to SPX as delta-hedged SVS using SSR of 1. This is because the delta calculated from BlackScholes does not take into account the increase in fixed strike implied volatilities when SPX declines. A more refined model, which takes into account the change in strike volatilities using SSR greater than 1, would have lower correlation to SPX.












FIGURE 14 Hedged SVS has low correlation irrespective of different regimes

FIGURE 15 Hedged SVS has low sensitivity to moderate SPX returns but declines significantly for large SPX returns SVS 1M Ret. Ret. 5%

Rolling 6M Correlation to SPX 100% 80%

0%

60% 40%

-5%

20% 0%

-10%

-20% -40%

-15%

-60% -80% Jan-96

Jan-00 Unhedged SVS

Jan-04

Jan-08

Jan-12

Hedged SVS (Rolling SSR)

Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital.

-20% -30%

-20%

-10% 0% 10% SPX 1M Ret. Unhedged Hedged (Rolling SSR)

Source: Barclays Research, OptionMetrics, Bloomberg Note: The SVS strategy sells 0.2 vega of 1M variance swap for $100 of capital.

Market Neutral Short VIX Futures Strategy As we have documented extensively in our regular publications (Systematic Volatility Monthly and The VIX Compass), a short position in VIX futures has historically resulted in attractive risk reward characteristics. This results from the premium that exists in the volatility term structure. In other words, the term structure of volatility tends to be too













Barclays | Special Report In Figure 16 16 and Figure 17, 17, we show the performance of an un-hedged and hedged short 1M VIX futures strategy. The strategy systematically shorts the front month VIX future and rolls it 10 days before expiration. We have sized the short VIX futures strategy to be equal to 0.4 vega per $100 in equity to make the draw-downs of short VIX futures strategy comparable to SVS. FIGURE 16 Hedged Short VIX futures strategy has very low standard deviation 130 120 110 100 90











Barclays | Special Report •

Similar to hedged SVS, the hedged short VIX futures strategy had low returns (-0.7%) in 2013 when equity markets rallied significantly.

FIGURE 18 Hedged short VIX futures strategy has low correlation in different periods Rolling 6M Correlation to to SPX 100%

FIGURE 19 Hedged short VIX futures strategy has low sensitivity to moderate SPX returns Short VIX future 1M Ret 5%

80% 60% 40% 20% 0%

0% -5% -10%

-20% -40% -60%

-15%












ANALYST(S) CERTIFICATION(S): I, Maneesh S. Deshpande, hereby certify (1) that the views expressed in this research report accurately reflect my personal views about any or all of the subject securities or issuers referred to in this research report and (2) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this research report.

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Barclays Special Report Market Neutral Variance Swap VIX Futures Strategies

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