Portfolio rebalancing based on time series momentum and downside risk

Abstract To examine the familiar tradeoff between risk and return in financial investments, we use a rolling two-stage stochastic program to compare mean-risk optimization models with time series momentum strategies. In backtest of allocating investment market index risk-free asset, generate scenarios future according momentum-based process model. A new hybrid approach, strategy controlling downside (TSMDR), frequently dominates traditional approaches by generating trading signals modified measure while setting risky asset position control conditional value-at-risk (CVaR) return. For insight into outperformance TSMDR, decompose each two aspects, signal allocation model that determines position. We find 1) weighted moving average can better capture trend stock than computed as past 12-month excess return, 2) strategies generally provide returns whereas parity have less 3) CVaR limits variance does.