Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations
UBS Investment Bank; Queen Mary, University of London; Imperial College Business School
Imperial College Business School; CEPR (Centre for Economic Policy Research); University of Oxford, Oxford-Man Institute of Quantitative Finance
October 1, 2015
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 1974 until 2013. We show that more efficient volatility estimation and price trend detection significantly reduce portfolio turnover and therefore rebalancing costs. The poor performance of time-series momentum strategies during the post-2008 period is explained by an increased level of pairwise correlations. We propose a novel correlation-based leverage-adjustment to the strategy's weighting scheme and show that it improves performance by safeguarding against tail risk, even after accounting for realistic transaction costs.
Number of Pages in PDF File: 46
Keywords: Trend-following, Momentum, Constant-volatility, Volatility-targeting, Trading rules, Pairwise correlations, Diversification, Transaction costs, Turnover
JEL Classification: E37, G11, G15, F37
Date posted: September 2, 2012 ; Last revised: October 12, 2015
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