Not surprisingly, quants tend to gravitate to options. For one thing, option pricing models can be mathematically challenging because, unlike stocks, options have a nonlinear payoff function. Sergey Izraylevich and Vadim Tsudikman, whom readers may have previously encountered through their contributions to
Futures Magazine, use quantitative methods to find profitable option trades. In Systematic Options Trading: Evaluating, Analyzing, and Profiting from Mispriced Option Opportunities (FT Press, 2010) they introduce the reader to techniques by which to calculate the difference between the market price of an option and its fair value. This difference represents a trading opportunity.
The authors explain the advantages of their approach over the traditional, admittedly tedious, route of using scanners, rankers, and payoff charts. The traditional method is a “differential approach. It is a forced measure resulting from the imperfection of analytical tools limited to simple scanning and visual analysis of payoff functions…. What [the authors] oppose to a differential approach is an integral systematic approach based on the strictly formalized assessment criteria, universal procedures of multicriteria analysis, and well-structured selection algorithms. The systematic approach enables simultaneous processing of a considerable number of option strategies and underlying assets. Without such an integral system, the investor has little or even no chance to make prompt selection decisions and to adapt successfully to changing market conditions.” (pp. xxiii-xxiv)
Izraylevich and Tsudikman develop a series of criteria to evaluate and compare individual options and their combinations; the higher the criterion value the better the profit potential. The primary criteria they use are: expected profit on the basis of lognormal distribution (EPLN), empirical distribution (EPEM), and symmetrized empirical distribution (EPES); profit probability on the basis of the same three distributions (PPLN, PPEM, and PPES); the ratio of expected profit to loss based on these distributions (RPLL, RPLE, and RPLS); the ratio of implied to historical volatility (IV/HV), and the break-even range (BEVR).
Not every criterion is equally effective for the four option strategies the authors consider here (long and short strangle/straddle, long and short calendar spread). They employ various indicators, such as the correlation between a criterion and profit indexes, the correlation between the Sharpe ratios of the criterion and profit, and the areas ratio, to measure their effectiveness. But, as the authors readily admit, these indicators just skim the surface: “Undoubtedly, a creative approach allows developing a lot of additional indicators based on various evaluation principles.” (p. 102)
Although most of the criteria, taken individually, “show statistically reliable predictive power, in most cases it is rather weak. Nevertheless, this small forecasting effect gives a considerable advantage to those who use it over those who ignore systematic criteria application. … Concurrent utilization of many criteria allows exploiting different individual advantages inherent to each of them. The cumulative synergetic effect of such a multifaceted approach is expected to be quite noticeable.” (p. 182) It is, of course, critical to measure the correlation between different criteria when pursuing a multicriteria strategy.
The reader who wants to replicate the authors’ work at home or expand on it will need, at the very least, an end-of-day database of option prices. A solid foundation in statistics and probability theory is also a prerequisite. And without some programming skills all those numbers (I just experimented with a sample download—a single day of strike prices for U.S. equities fills some 300,000 lines in an Excel spreadsheet, which is of course not where the data should be housed) will be unmanageable. The ill-equipped or lazy reader can go to the book's website for daily updates on trading opportunities using single criteria for straddles and strangles, calendar spreads, butterflies, and condors.