Demystifying Time Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations
Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time series momentum strategies on their turnover and performance from 1984 until 2013. We show that more efficient volatility estimation and price trend detection can significantly reduce portfolio turnover by more than one third, without causing a statistically significant performance penalty. We shed light on the post 2008 underperformance of the strategy by linking it to the increased level of asset co movement. We propose a novel implementation of the strategy that incorporates the pairwise signed correlations by means of a dynamic leverage mechanism. The correlation adjusted variant outperforms the naive implementation of the strategy and the outperformance is more pronounced in the post 2008 period. Finally, using a transaction costs model for futures based strategies that separates costs into roll over and rebalancing costs, we show that our findings remain robust to the inclusion of transaction costs.