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Chinese Journal of Management Science ›› 2024, Vol. 32 ›› Issue (8): 50-60.doi: 10.16381/j.cnki.issn1003-207x.2022.1429

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Asset Pricing Based on the Optimal Idiosyncratic Return Factor

Xuanming Ni1,Tiantian Zheng1,Huimin Zhao2(),Kangping Wu3   

  1. 1.School of Software and Microelectronics, Peking University, Beijing 100871, China
    2.School of Business, Sun Yat-sen University, Guangzhou 510275, China
    3.School of Economics and Management, Tsinghua University, Beijing 100084, China
  • Received:2022-06-30 Revised:2022-12-18 Online:2024-08-25 Published:2024-08-29
  • Contact: Huimin Zhao E-mail:zhaohuim@mail.sysu.edu.cn

Abstract:

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 ability 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.

Key words: asset pricing, factor model, idiosyncratic return, portfolio optimization, missing factor identification

CLC Number: