Asset Pricing Based on the Optimal Idiosyncratic Return Factor
Starting from the idiosyncratic returns of the classical factor model,an idiosyncratic return factor is constructed by optimizing the portfolio in the residual space to identify the missing information in the benchmark model,so as to price the idiosyncratic returns under the benchmark and improve the benchmark.Furthermore,the pricing ability of the extended factor is proved through mathematical derivation.Next,based on 6 factor datasets of A shares from 1995-01 to 2022-11 and 4 factor datasets of the US stocks from 1963-07 to 2022-10,the idiosyncratic return factor is added to three-factor,four-factor,and five-factor models,and the pricing abil-ity of the expanded models is compared with their benchmarks,the mean-variance efficient(MVE)model,and the principal component analysis(PCA)model.The empirical results show that after adding the idiosyncratic return factor,the GRS statistic and t-statistic are greatly reduced,and the pricing ability of the original model is significantly improved,better than the MVE model and the PCA model in most cases.These results hold both in-sample and out-of-sample,for A-share and the US stock markets,indicating the robustness and adaptability of the idiosyncratic return factor.
万方数据
维普
