Smart Stochastic Discount Factors
提出了一个无套利框架，用于在存在交易摩擦的市场中构建满足凸定价约束的随机贴现因子，并发现最小方差SDF能有效平衡时间序列与横截面拟合。
We provide a no-arbitrage framework for stochastic discount factors (SDFs) that satisfy convex pricing constraints in markets characterized by a wide range of trading frictions. We demonstrate a duality relationship connecting minimum dispersion SDFs to portfolio optimization problems with penalty functions directly capturing the underlying frictions. Empirically, we examine how mispricing impacts the SDF’s effectiveness in explaining both cross-sectional and time series variation in asset returns. We find that a minimum-variance SDF, constructed by combining the capital asset pricing model SDF with a portfolio that constrains the mispricing of nonmarket risks, achieves a favorable tradeoff between time series and cross-sectional fit. This paper was accepted by Kay Giesecke, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05750 .