Improving Time-Series Momentum Strategies: The Role of Trading Signals and Volatility Estimators

Akindynos-Nikolaos Balta, Robert Kosowski: Constructing a time-series momentum strategy involves the volatility-adjusted aggregation of univariate strategies and therefore relies heavily on the efficiency of the volatility estimator and on the quality of the momentum trading signal.

Author(s) :

Akindynos-Nikolaos Balta

Imperial College Business School

Robert Kosowski

EDHEC Business School

Presentation :

Using a dataset with intra-day quotes of 12 futures contracts from November 1999 to October 2009, we investigate these dependencies and their relation to time-series momentum profitability and reach a number of novel findings. Momentum trading signals generated by fitting a linear trend on the asset price path maximise the out-of-sample performance while minimising the portfolio turnover, hence dominating the ordinary momentum trading signal in literature, the sign of past return. Regarding the volatilityadjusted aggregation of univariate strategies, the Yang-Zhang range estimator constitutes the optimal choice for volatility estimation in terms of maximising efficiency and minimising the bias and the ex-post portfolio turnover.
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Improving Time-Series Momentum Strategies: The Role of Trading Signals and Volat...
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Type : Working paper
Date : le 06/08/2012
Extra information : For more information, please contact EDHEC Research and Development Department [ research@drd.edhec.edu ]
Research Cluster : Finance

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