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Are the Fama–French factors good proxies for latent risk factors? Evidence from the data of SHSE in China

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  • Lin, Jianhao
  • Wang, Meijin
  • Cai, Lingfeng

Abstract

This paper applies the new procedure developed by Bai and Ng (2006a) to explore the relation between the Fama–French factors and the latent risk factors in China’s stock market. The results show that the Fama–French factors are good proxies for risk factors of portfolios. For individual stock, only the Market factor is appropriate to proxy risk factors, while the other proxies we consider are not.

Suggested Citation

  • Lin, Jianhao & Wang, Meijin & Cai, Lingfeng, 2012. "Are the Fama–French factors good proxies for latent risk factors? Evidence from the data of SHSE in China," Economics Letters, Elsevier, vol. 116(2), pages 265-268.
  • Handle: RePEc:eee:ecolet:v:116:y:2012:i:2:p:265-268
    DOI: 10.1016/j.econlet.2012.02.026
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    References listed on IDEAS

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    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
    3. Bai, Jushan & Ng, Serena, 2006. "Evaluating latent and observed factors in macroeconomics and finance," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 507-537.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    6. Shanken, Jay, 1992. "On the Estimation of Beta-Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 1-33.
    7. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    8. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    9. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
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    Cited by:

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    4. Tong Fang & Zhi Su & Libo Yin, 2021. "Does the green inspiration effect matter for stock returns? Evidence from the Chinese stock market," Empirical Economics, Springer, vol. 60(5), pages 2155-2176, May.
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    7. Lanlan Liu & Dan Luo & Liang Han, 2019. "Default risk, state ownership and the cross-section of stock returns: evidence from China," Review of Quantitative Finance and Accounting, Springer, vol. 53(4), pages 933-966, November.

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    More about this item

    Keywords

    Fama–French factors; Latent risk factors; Proxies; Principal components;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services

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