Volatility filter for index tracking and long–short market-neutral strategies

Abstract

Trading strategies utilising price co-movements between financial assets often require that underlying portfolios have high correlations with certain benchmarks and low tracking errors. Since correlations among financial assets are known to be time varying, these portfolios need to be rebalanced dynamically to maintain high ‘tracking efficiency’. The presence of transaction costs, however, prohibits investors from switching market positions too often. It is well known that correlations between equities tend to increase when market volatility is high. The primary objective of this paper is to apply volatility confirmation filters to dynamic index tracking, and long–short market-neutral trading, to enhance the performance of such strategies after transaction costs. In particular, I propose a dynamic rebalancing scheme where the underlying market volatility functions as a timing device and tracking portfolios are only rebalanced when the underlying volatility regime changes. Tracking portfolios studied are optimised by minimising three widely used tracking error measurements: tracking error variance (TEV), mean absolute deviation (MAD) and mean error (ME). Empirical results show that the addition of the volatility filter improves on the excess returns generated from the index tracking strategy. The trading performance of the long–short market-neutral strategy is also significantly enhanced with such a filter in terms of annualised return, annualised volatility and the risk-adjusted Sharpe ratio.