Reversal strategies

[John Seekers]

In this research note we investigate whether short-horizon, statistical arbitrage style alpha factors perform differently in different environments. In particular it is often said that stat arb strategies are “long vol” in the sense that they profit when market level volatility measures are higher than average. We find that reversal strategies perform best in high-volatility environments, but that both reversal and other short-horizon technical trading strategies perform best when the opportunity set – as measured by the cross-sectional variance of returns – is highest.

The opportunity set measure better distinguishes a priori between low- and high-performing periods for reversal, does so for the three other subcomponents of ExtractAlpha’s Tactical Model (TM1), and is a more stable measure than the VIX. Current opportunity set measures favor stat arb strategies.

[John Seekers]

We provide a practical and technical overview of volatility trading strategies:
1) The insight for the design and back-testing of systematic volatility strategies
2) Understanding of risk-reward trade-off and potential pitfalls of volatility strategies

We focus on systematic and rule-based trading strategies that can be marketed as an investable index or a proprietary strategy:
1) Delta-hedged strategies for capturing the volatility and skew risk-premiums
2) Without delta-hedge: CBOE and customized options buy-write indices

We overview important implementation aspects:
1) Measuring the historic realized volatility
2) Forecasting the expected realized volatility
3) Measuring and forecasting implied and realized skew
4) Computing option delta consistently with empirical dynamics
5) Analysis of transaction costs
6) Managing the tail-risk of short volatility strategies