Variable Selection for Portfolio Choice
研究在收益条件矩部分可预测时如何直接确定最优投资组合权重对预测变量的依赖关系，通过将预测变量组合成单一指数来捕捉投资机会的时变特征，帮助投资者决定应跟踪哪些经济变量及其组合方式。
We study asset allocation when the conditional moments of returns are partly predictable. Rather than first model the return distribution and subsequently characterize the portfolio choice, we determine directly the dependence of the optimal portfolio weights on the predictive variables. We combine the predictors into a single index that best captures time variations in investment opportunities. This index helps investors determine which economic variables they should track and, more importantly, in what combination. We consider investors with both expected utility (mean variance and CRRA) and nonexpected utility (ambiguity aversion and prospect theory) objectives and characterize their market timing, horizon effects, and hedging demands.