改进时间序列动量策略——交易信号和波动率估计的作用

Abstract
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. 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.