Arbitrage Portfolios
提出一种利用公司特征构建套利组合的新方法，该方法优先将预测能力归因于风险因素，再归因于异常收益。应用于模拟经济和美国股票数据，发现套利组合相对多个流行定价模型有显著alpha，年化夏普比率在1.31到1.66之间。
Abstract We propose a new methodology for forming arbitrage portfolios that utilizes the information contained in firm characteristics for both abnormal returns and factor loadings. The methodology gives maximal weight to risk-based interpretations of characteristics’ predictive power before any attribution is made to abnormal returns. We apply the methodology to simulated economies and to a large panel of U.S. stock returns. The methodology works well in our simulation and when applied to stocks. Empirically, we find the arbitrage portfolio has (statistically and economically) significant alphas relative to several popular asset pricing models and annualized Sharpe ratios ranging from 1.31 to 1.66.