Sep 9, 2014

Weekly Options Selling, and Time-Risk Blindness

I would like to start today's post with a quote from a recent article discussing risk of earthquakes:

Even if we can comprehend a 30-percent chance of rain, or near-term odds like a coin flip, low-probability events are different. They have a “bewildering” effect on people, says Howard Rachlin, a professor emeritus of psychology at Stony Brook University. So we tend to lump them together; 1 in 10,000 sounds just as bewildering as 1 in 100,000. This is why people buy lottery tickets, even though the likelihood of winning is outrageously less likely than an event like a big earthquake in a seismically active region.
“All low chances seem the same,” Rachlin says.
When it comes to living our lives today or making plans for next weekend, behaving as if low probability is essentially zero chance isn’t necessarily a bad thing. We would be paralyzed otherwise.
But stretch that low probability over time — which is how earthquake risk is estimated — and confusion with low probabilities morphs into complete incomprehension. If you live in an earthquake-prone place for 10,000 days, the cumulative probability gets higher and higher, approaching 1 in 1. Our minds, unfortunately, have a hard time keeping up.
“We don’t see how these small things add up when you do them over and over again,” says Fischhoff. In study after study—looking at compound interest, unsafe sex, driving without a seatbelt, floods, earthquakes — we underestimate such cumulative effects. It’s one of those cognitive shortcomings calling out for a name. Maybe it should be called something like time-risk blindness. From The Aftershocks by David Wolman.

Recently I have noticed a marked increase in the number of short volatility trading systems offered by vendors, and specifically trading strategies that sell weekly options. While short vol strategies have enjoyed certain popularity, they have grown (at least from what I see on the web) with increased liquidity and higher number of names in weekly options.

I will admit right away that I am not a fan of vendor strategies, especially in options, simply because disparate incentives between vendor and customer. Vendors usually charge fixed fees (usually monthly fees of $30-$100) for signals and recommendations that customer is supposed to execute in their own account. While vendor does not participate in the upside or downside of the trades they recommend, they cannot help but to want to keep their customers paying as long as possible. This is generally a good thing, but we should remember that these strategies are likely to be short-vol strategies - steady returns, low vol until vol spikes up.

This effect is particularly strong in weekly options, and I think is exacerbated by the time-risk blindness mentioned above. Vendors suggest profits of 1% per trade ( per week - 64% compounded after a year of trading ) implying approximately 1 in 100 "fair" chance of losing 100% of the account. Since 1 in 100 is 1 in 2 years of trading, this gives sufficient time for a vendor to build up a pretty chart and start collecting fees. This is also long enough for a client to start forming the time-risk blindness about real risks of the strategy.

In summary: please be extra careful about short-vol strategies with weekly options. It is very difficult to properly understand and appreciate the risks of such strategies.

Jul 29, 2014

VKOSPI Futures Update

According to a recent article in Risk magazine Korea's Financial Services Commission is planning to introduce volatility futures on VKOSPI index sometime before the end of the year. It has been for quite sometime in the planning stage ( I first wrote about it 2.5 years ago ) but the product may finally come to the market. Given lack of liquidity in other Asian volatility futures I am pessimistic about the product attracting volume.

Jul 28, 2014

Reliability of the Maximum Drawdown

I recently came across an old article titled Reliability of the Maximum Drawdown, and suggest that trades familiarize themselves with the ideas mentioned there. I would like to suggest an idea that may be a way forward.

The mathematics of maximum drawdown (expected maximum drawdown, and its distribution) are far from trivial, and many other related measures (for example expected length of drawdown) afaik have not been seriously studied at all.

The problem with max-measures, like mentioned in the article above, is that they are extreme measures, and thus are at the very corner of distribution charts. If you have a strategy that suffered a maximum drawdown of x% you know that such drawdown is possible, but if you observe another strategy with smaller drawdown, you can hardly be sure that it will not suffer from a greater drawdown in the future.

One possible way forward is to use "average measures" - average drawdown and average drawdown length instead of their max counterparts. Intuition suggests (and my extensive monte carlo confirms) that these measures have smaller variability,  smaller skewness, and more predictive (as measured by linear and nonlinear correlations) from one period to the next. These measures seem to scale linearly with time, with the scale coeffcient depending on kurtosis. I don't have the maths to take this much further on my own, but if you have some ideas please leave a comment or send me an email.