Bayesian Alphas and Mutual Fund Persistence
用日收益率数据比较贝叶斯估计与标准频率派方法对共同基金业绩的预测能力，发现当非基准资产收益率与基金持仓相关时，贝叶斯阿尔法能更好预测未来业绩，且对管理者技能持适度乐观的先验更符合投资者资金流向。
ABSTRACT We use daily returns to compare the performance predictability of Bayesian estimates of mutual fund performance with standard frequentist measures. When the returns on passive nonbenchmark assets are correlated with fund holdings, incorporating histories of these returns produces a performance measure that predicts future performance better than standard measures do. Bayesian alphas based on the Capital Asset Pricing Model (CAPM) are particularly useful for predicting future standard CAPM alphas. Over our sample period, priors consistent with moderate to diffuse beliefs in managerial skill dominate more skeptical prior beliefs, a result that is consistent with investor cash flows.