Enhanced Global Asset Pricing Factors
构建并检验了增强的全球回报因子，通过三种方法（协方差结构信息、波动率降低技术、分散化收益）提升夏普比率，平均比传统因子提高1.96倍，对资产定价研究有参考价值。
Abstract This article constructs and examines enhanced global return factors. I focus on three different enhancement approaches. First, I incorporate information about the covariance structure in the cross-section of stock returns. Second, I employ volatility-reducing techniques in the time series. Third, I exploit diversification benefits. I form six categorical factors by aggregating information from 214 characteristics. Further, I diversify across factors. The enhancement mechanisms are largely successful and when jointly applied increase the optimal Sharpe ratio on average by a factor of 1.96 compared to the traditional factors. My results point to the importance of employing efficient factors in asset pricing studies.