Global Sigma Group, St Crispin's Day Speech

Global Sigma Group, a volatility fund with almost 6 years track record in S&P options is preparing a new offering called BondVol, with focus on Treasuries vol. New information, although quite sparse, is available on their website, as well as this SEC filing. One interesting point is -86% correlation between Sigma Plus and BondVol funds, but I believe this to be a statistical fluke - knowing the factor drivers of such strategies I believe that long-term correlation will be positive, and significant, probably at +50%.

The (unconfirmed) rumor is that the flagship Global Sigma Plus Program is suffering their largest drawdown to date, although my understanding is that it is significant, but within  reason. I know a many people in volatility space, and August has been difficult for many, and everyone knows that they can't all be winners. So, fellow traders - hedge your deltas, and good luck in September. Remember, you may have lost money, but not ability to make money.

Capstone Is Having A Great Month

According to today's article in Business Insider Australia, Capstone (largest dedicated volatility trading hedge fund) is having a great month.

"One of the smaller funds in the firm’s tail risk strategy has delivered a 55% return so far this month, according to a person familiar with the fund’s returns. Across that strategy, Capstone manages $US600 million. The 55% is for one of those funds.

The firm’s bigger $US3 billion flagship volatility arbitrage fund return 1.2% so far in August, according to the person."

The rest of the article is hand wavy explanation of volatility and trading.
I don't have access to Capstone returns, so these numbers are interesting, to analyze and compare to how other vol funds did in August.

More on CBOE's Buy-Write Indexes

As I mentioned in the previous post, it is not easy to separate real alpha, from mean-median difference in short gamma strategies. Since buy-write strategies are short gamma, it is not surprising that they show alpha in regression. This is the table that I calculated in the previous post.

Symbol	Start Date	Annualized Alpha	Beta SPX	Alpha t-stat
BXM	30-Jun-86	3.8%	0.66	3.88
BXMC	31-Jan-90	4.5%	0.69	4.75
BXMD	30-Jun-86	4.1%	0.83	4.60
BXMW	29-Jun-12	2.3%	0.61	1.57
BXY	1-Jun-88	4.3%	0.76	4.40

How will these results change if we add another (systematic short volatility) factor into regression. For that factor I will use CBOE's own PUT index, which sells monthly atm puts.

Symbol	Start Date	Annualized Alpha	Beta SPX	Alpha t-stat
BXM	30-Jun-86	0.3%	0.25	0.66
BXMC	31-Jan-90	0.7%	0.29	1.31
BXMD	30-Jun-86	1.8%	0.57	2.57
BXMW	29-Jun-12	2.0%	0.29	2.10
BXY	1-Jun-88	0.8%	0.41	1.16

As we can plainly see, adding PUT as factor significantly reduces alphas, and their t-stats. Not only BXM - which is by construction (pretty much) a linear combination of PUT and SPX has no alpha, but also other benchmark "innovations" -  BXMC (conditional) or BXY (2% otm) do not provide any meaningful alpha. The only two benchmarks standing out now is BXMW - which has relatively short history, and BXMD (30-delta buy-write).

Quick Note on CBOE's Buy-Write Indexes

Last month CBOE expanded their portfolio of benchmark indexes, adding 10 more new ones. Link to the press release. I would not be surprised that some people will look at these benchmarks as complete trading strategies, however one should be careful as such benchmark indexes are often just an exercise in overfitting until desired result (pretty chart) can be produced.

Such datamining error is especially easy with options. Short strategies tend to produce "good" results that seem like a legitimate alpha, when in reality it is just the median returns are high, and average returns looks much worse, i.e. the strategy negatively skewed. Even when one is using a long dataset, for example including the crisis of 2008, it is too easy to add a moving average filter, or change parameters in such a way as to create good results.

Separating legitimate alpha, especially short volatility alpha from what is generally referred to "volatility risk premium" is difficult. I believe if one is facing such task, the process should be both quantitative and qualitative, checking that the strategy makes sense on the logical level. Here I will not try to perform any thorough analysis but will just add a few notes and ides on the new benchmarks.

As I mentioned above there were total of 10 new strategies, 9 based on SPX, and one based on VIX. Complete list of CBOE benchmarks is available here. I will start with buy-write indexes, but will write about other benchmarks in later posts.

"The CBOE S&P 500 Multi-Week BuyWrite Index is designed to track the performance of a hypothetical weekly covered call strategy with staggered short positions in call options expiring in consecutive four week options.  The BXMW Index is constructed as a combined portfolio of four mini BuyWrite indexes.  Expirations are staggered so that the BXMW Index sells four-week options on a rolling weekly basis. "

This is a very recent index, and CBOE obviously tried to generalize the "original" Buy Write by using weeklys. In-samples statistics are robust - the benchmark delivers about 2% annualized alpha, with 0.6 beta to SPX.  Of course it is more interesting is writing weeklys is better than writing regular monthly options, so let's compare BXMW to BXM.

And indeed the weekly buy write outperforms BXM - alpha (to BXM, not SPX) is 3% annualized with beta of about 0.9. Most of the outperformance comes from two periods: in the end of 2012 and most recently in October of 2014. The drawdowns seems to be about the same, however BXMW has stronger rebounds than BXMW.  Below are all three indexes for comparison.

"The CBOE S&P 500 30-Delta BuyWrite Index is designed to track the performance of a hypothetical covered call strategy that holds a long position indexed to the S&P 500 Index and sells a monthly out-of-the-money (OTM) S&P 500 Index (SPX) call option. The call option written is the strike nearest to the 30 Delta at 10:00 a.m. CT on the roll date.  The BXMD Index rolls on a monthly basis, typically every third Friday of the month. "

BXMD writes a call that is father OTM than the original BXM. Not surprisingly alpha is higher - or let's say full premium is collected more often, alpha in the regression is higher, not necessarily true alpha. Beta is higher, as expected. Another very similar index is BXY, which uses 2% instead of 30-delta rule. BXY does just a tiny bit worse than BXMD, but the difference is not significant, so I will not include the chart.

"The CBOE S&P 500 Conditional BuyWrite Index is designed to track the performance of a hypothetical covered call strategy that holds a long position indexed to the S&P 500 Index and sells a monthly at-the-money (ATM) S&P 500 Index (SPX) call option. The written number of ATM call options will be either ½ unit or 1 unit and will be determined by the level of the CBOE Volatility Index (VIX Index) when the call option is written on the roll date.  The BXMC Index rolls on a monthly basis, typically every third Friday of the month. "

BXMC writes more or less options depending in the VIX level. It is not a surprise that adding this rule improves performance with alpha of 4% and beta of 0.7. 

Symbol	Start Date	Annualized Alpha	Beta	Alpha t-stat
BXM	30-Jun-86	3.8%	0.66	3.88
BXMC	31-Jan-90	4.5%	0.69	4.75
BXMD	30-Jun-86	4.1%	0.83	4.60
BXMW	29-Jun-12	2.3%	0.61	1.57
BXY	1-Jun-88	4.3%	0.76	4.40

There is really nothing surprising about these summary stats - beta < 1, alpha > 0 (otherwise there would be no benchmark), and ones with more rules make more alpha. However selling otm index calls (against the skew) is obviously risky in the run-away bull market like we had in the past few years. So let's see how the benchmarks fared over the most recent period (same as BXMW which has the shortest history)

Symbol	Start Date	Annualized Alpha	Beta	Alpha t-stat
BXM	29-Jun-12	-0.9%	0.65	-0.51
BXMC	29-Jun-12	-0.4%	0.80	-0.32
BXMD	29-Jun-12	-0.9%	0.81	-0.59
BXMW	29-Jun-12	2.3%	0.61	1.57
BXY	29-Jun-12	-1.8%	0.85	-1.17

I guess this is really the main reason for introduction of the BXMW - it is the only benchmark to beat SPX! To be honest, I am not sure why this is so - why is monthly sale worse than 4 weekly sales? What is it in the skew that would explain this outperformance? I don't know - and I would not really put much trust that this recent performance by BXMW is robust. I do not believe that there is sufficient evidence that buy-write indexes are delivering true alpha - or enough alpha to justify beta risk. 

For further reading (and more optimistic view) I recommend this recent article. 

YLDVOL - Better Fixed Income Volatility Index

By all accounts CBOE's VXTYN Index has been a bust in terms of market participation. Currently the front month contract has zero volume, and zero open interest. This is where Triple 3 Partners, Australia-based hedge fund manager specializing in volatility trading, is hoping to step in.

They have developed an alternative index YLDVOL (Bloomberg ticker YLDVUST) that i s supposed to better represent hedging and speculation needs of fixed income traders. YLDVOL has been developed under guidance of Dr Peter Carr from academic side, and in consultation with many fixed income traders.

What traders complained about, is that CBOE just took their existing (admittedly very successful) VIX Index formula, and copied and pasted it to treasury market, ignoring specific differences between equities and FI. The differences are far from superficial - while equities volatility is typically quoted in %s, FI vol is quotes in basis points. This is really not just about the denominator, percent vol presumes geometric process (like geometric Brownian motion) while points vol presumes arithmetic process (like "regular" arithmetic Brownian motion). Therefore it would make sense that instead of VAR-Swap formula that is used for VIX index, YLDVOL would use Bachelier's implied vol. Just like the VIX, YLDVOL is interpolated to a constant 30-day maturity.

Details on the index, and index calculations are available on t3index.com, and live values on Bloomberg using YLDVUST Index. A look-alike index based on BUND with Bloomberg ticker YLDVBUND Index.