Below is an interview excerpt for web site members before the article is published in the upcoming Opalesque Futures Intelligence. Here is a link to a performance sheet of the CTA: Global Sigma
Recent Pinnacle award winner Hanming Rao is Chief Investment Officer for Global Sigma Plus, a short option trading system in the S&P 500 markets. A Harvard PhD and former SAC Capital and Millennium Partner trader, Dr. Rao engages in what for some is a controversial trading strategy: selling option premium on the S&P 500 futures.
The strategy works by selling “out of the money” options and collecting a set premium from the option buyer at the time of the trade. The option buyer is seeking to hedge against a stock market decline and thus pays a premium for the “insurance.” The pricing of the option premium is dictated based on a number of factors, but most significantly volatility in the markets traded, time horizon relative to expiration and the distance the option is sold from the current market price. The trade profit is defined by the option premium collected while the primary risk is that the options sold move higher in price and close “in the money.” A loss example might be selling an S&P 500 put before a market crash and having the value of the put rise significantly afterwards. The loss on the trade is defined by the difference between the initial option sale price and the now higher closing price of the option.
Global Sigma Plus has an interesting track record and Dr. Rao is well versed in market strategy, yet the risk management regime has yet to be tested during a period of market crisis. Past performance is not indicative of future results. There is risk of loss when investing in managed futures. This interview does not constitute a recommendation to invest. Performance data supplied by the CTA and was not audited by this publication.
With under $89 million in assets under management, the short option strategy employed by Dr. Rao is known to have a higher average win percentage than trend or relative value strategies, in several studies known to average around 74%. The analytical value of win percentage in this strategy, however, might be considered a red herring. As noted in the interview below, risk management – particularly during market crisis – can be significant. Investors analyzing risk in this strategy might do well to consider worst drawdown and downside deviation as clues to risk control, with particular emphasis on drawdown mitigation during periods of rising volatility. In P (A|B) Method analysis, one benchmark CTA in this category used for comparison is LJM Partners who has a track record dating back 1998, operating during periods of multiple crisis with nearly $200 million in total firm assets under management. We recently caught up with Dr. Rao after his winning the Pinnacle Award for best emerging CTA:
Mark Melin (MM): Can volatility, a key driver of profit and loss in this strategy, be predicted? Past study of volatility has indicated that occurrences are randomized. If it can be predicted, what are you looking at? Do the variables in your formula have validity?
“Volatility is very mean reverting and range bounded”
Hamning Rao (HR): Volatility is very mean reverting and range bound. The average VIX price for the past 20 years has been around 20. In comparison, the S&P500 doubled in value over the last ten years and quadrupled from 1993 to 2013. I don’t know where S&P500 will be for the next 10 years, but it is my opinion the average VIX will most likely still be around 20.
“Many people say stock markets are random. If the market is random, there won’t be fat tails.”
Many people say stock markets are random. On the other hand, everyone is talking about fat tails. These two things cannot exist at the same time. If the market is random, there won’t be fat tails.
The reason for fat tails, in my opinion, is due to investors herd mentality and risk averse nature of human being. Long term stock market price direction is moved by fundamentals but short term it is a “voting machine.” That is why economists love long term forecasts and technical analysts love short term plays. From technical stand point of view, it is hard to forecast long term movement because there are too many variables. This is more like butterfly effect: there was a butterfly flapping its wing in Brazil, then you had a tornado in Oklahoma City. You may say the butterfly caused the tornado, but they were too far apart and too many things could happen in the middle, it was hard to draw the conclusion. However, the federal agents warned residents 36 minutes before the tornado. So it’s no longer unpredictable when it’s close. Same thing in the financial markets, in summer 2008, most people believed Lehman would survive. However, the Friday before Lehman filed bankruptcy, people knew either Lehman would be bought by another bank or it would disappear. You only have two choices then and the market quickly priced in what would happen next. I could even argue 911 was not random. You had Airlines sold off unusually hard and VIX climbed 11 points to 32 during the 10 trading days before the attack. It was quite a warning already.
MM: Describe your strategy.
HR: Like many option programs, we also sell options to collect premium. The difference is we may hedge our risk exposure using future aggressively. We try to manage risk on a day to day basis and try to minimize our draw down. We focus on shorter time frame and we can only sell options within 6 weeks to expiration. We also trade very frequently — we traded 20,000 contracts per year per million dollars for 2012 (a high level of trading, which potentially indicates a fair amount of hedging activity). If the strategies work, higher turnover is helpful to minimize draw downs.
MM: Are you 100% discretionary or is there some formula or process you utilize?
We had models and back tests. But trading and execution are discretionary. Compared to futures markets, it is very hard to automate options trading. You had hundreds of strikes and multiple-expiry compare to one single number of underline futures. So far we feel discretionary trading is fine and don’t plan to change it.
MM: What is your edge?
“The only way to distinguish option sellers was when market tanked or had big spikes. It is like what Warren Buffet said: ‘Only when the tide goes out do you discover who’s been swimming naked.’ In order to generate consistent returns over time, you need to focus on risk management.”
HR: We think we have a better risk control. Generating returns in an option strategy is the easy part. Everyone knows how to sell options. When market is range bounded, both good traders and bad traders make money. Traders without strong risk management actually will make more money. Like in 2012, the S&P500 index didn’t have a big movement compared to 2010 or 2011, and almost every option sellers made nice profit. The only way to distinguish option sellers was when market tanked or had big spikes. It is like what Warren Buffet said: ”Only when the tide goes out do you discover who’s been swimming naked.” In order to generate consistent returns over time, you need to focus on risk management. We optimized our program based on risk adjusted return instead of maximum return. We hedge our risk aggressively when we have draw downs — since big draw downs are not 0 to 1 switch. Big draw downs always followed by smaller draw downs. So you need cut loss aggressively even when you have smaller draw downs.
MM: What happens when the VIX is at very low levels? Are their points at which you don’t enter the market? Do you sit on the sidelines?
“It is very hard to make money when the VIX is low.”
HR: It is very hard to make money when the VIX is low. Obviously if VIX ever went 0, we would close shop since there would be no premium to collect. Our expected return is positively correlated to VIX. When the VIX is higher, we could collect more premium and generate higher returns. We don’t have a set target of returns because this variable. However, since VIX averaged 20 over the past 20 years, we expect 20% returns over longer period of time.
We typically are in the markets. Very occasionally we may be out of the market when realized volatility is higher than implied volatility or when we believe market is going to have a big jump in volatility.
MM: You work on the S&P, are you selling calls and puts or just puts? How do you determine distance from the money? Is there a volatility based formula or is it a standard deviation from the market?
HR: We trade both calls and puts. We typically choose options that have around 95% of chance to expire out of money. It is based on volatility. (It is interesting to note the CTA’s reported win percentage is up near 95%, well above the strategy average of the mid 70% range yet the track record is still only a few years old.)
MM: Describe how you enter positions (with this strategy it is interesting to note if they scale / leg in positions separately or enter the order as a strangle).
HR: We usually sell puts and calls separately instead of selling a strangle. We also spread out our orders and establish positions gradually instead of one big order.
MM: Address your risk controls. When unexpected volatility strikes, how does the risk management work? Are you hedging with futures or option spreads? Do you sell into the back month and roll the position? What might an investor benchmark relative to expectations when volatility strikes?
HR: When the VIX spikes, we usually short futures to hedge. Sometimes we also buy options to hedge as well. We don’t sell into the back month or roll the positions. We don’t like roll. We are memory-less. We mark to market everyday and use the settlement price as our cost for next day. Our mandate is to manage day to day risk. When you think about a roll to the forward month, you basically refuse to take loss on your positions. We believe that is not helpful in short term trading. Your trading decision should not be affected by your entry point cost.
When Volatility strikes, obviously our existing positions may lose money. But losing money may not be a bad thing because you will gain opportunities (by selling into the volatility spike into forward months) to boost returns the following month.
MM: What’s your margin to equity levels during a normalized market environment and what is the worst case extreme during a volatile market environment?
HR: We normally use 40% margin to equity based on CME SPAN margin and may spike to 80% in rare occasions. This is high compared to other CTA programs. (Editor: by comparison, the average margin to equity for trend traders typically hovers near 15%). One reason is CME imposed higher margin for equity index product compare to other commodities like Currency, Agriculture and Metals even though they have higher volatility. So just looking at margin to equity ratios is not fair for Equity index products.
[Risk Disclosure: Past performance is not indicative of future loss. Hypothetical past performance, such as modeling performance during previous market environments, is considered to be of lesser analytical value than a CTA’s track record trading client capital.]
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