Dynamic Trading with Predictable Returns and Transaction Costs
推导了交易成本存在且收益率可由不同均值回归速度的信号预测时的最优动态投资组合策略，发现最优策略是向一个加权平均的“目标组合”部分调整，慢速信号权重更大，并在商品期货中验证了其优于简单基准的净收益。
ABSTRACT We derive a closed‐form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean‐reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current aim. Specifically, the optimal updated portfolio is a linear combination of the existing portfolio and an “aim portfolio,” which is a weighted average of the current Markowitz portfolio (the moving target) and the expected Markowitz portfolios on all future dates (where the target is moving). Intuitively, predictors with slower mean‐reversion (alpha decay) get more weight in the aim portfolio. We implement the optimal strategy for commodity futures and find superior net returns relative to more naive benchmarks.