Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations
Akindynos-Nikolaos (Nick) Baltas
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
January 16, 2015
Motivated by the recent asset pricing literature that examines the effect of frictions on asset prices, we examine the effect of volatility estimator, trading rule choice and correlation-based leverage-adjustment on turnover and after transaction costs performance of time-series momentum strategies from 1974 until 2013. Range-based volatility estimators with desirable theoretical properties improve the performance of the strategies after transaction costs. Price trend-based momentum trading rules lead to the highest out-of-sample performance, because they significantly reduce portfolio turnover. Lastly, we explain why using a weighting scheme that incorporates correlations can improve net of transaction costs performance during the post 2008 financial crisis period.
Number of Pages in PDF File: 52
Keywords: Trend-following, Momentum, Constant-volatility, Volatility-targeting, Volatility-timing, Volatility estimation, Trading rules, Correlation, Diversification, Transaction costs, Turnover
JEL Classification: G11, G12, C13, C22working papers series
Date posted: September 2, 2012 ; Last revised: January 16, 2015
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