Measuring the Pricing Error of the Arbitrage Pricing Theory
提出一个贝叶斯框架，用吉布斯采样法得到套利定价理论中定价偏差的后验分布，并用行业和市值分组的月度组合回报数据发现，加入第一个因子后，再多加因子对减少定价误差帮助不大。
This article provides an exact Bayesian framework for analyzing the arbitrage pricing theory (APT). Based on the Gibbs sampler, we show how to obtain the exact posterior distributions for functions of interest in the factor model. In particular, we propose a measure of the APT pricing deviations and obtain its exact posterior distribution. Using monthly portfolio returns grouped by industry and market capitalization, we find that there is little improvement in reducing the pricing errors by including more factors beyond the first one.