A Semiautoregression Approach to the Arbitrage Pricing Theory
提出一种半自回归方法来估计套利定价理论中的因子，该方法能提供简单的渐近方差-协方差矩阵，便于调整测量误差。研究发现APT比CAPM稍好地描述资产回报，但仍有错误定价，且因子溢价随时间随商业周期变量变动。
ABSTRACT This paper developes a semiautoregression (SAR) approach to estimate factors of the arbitrage pricing theory (APT) that has the advantage of providing a simple asymptotic variance‐covariance matrix for the factor estimates, which makes it easy to adjust for measurement errors. Using the extracted factors, I confirm the finding that the APT describes asset returns slightly better than the CAPM, although there is still some mispricing in the APT model. I find that not only are the factors “priced” by the market, but the factor premiums move over time in relation to business cycle variables.