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Examination and Modification of Multi-Factor Model in Explaining Stock Excess Return with Hybrid Approach in Empirical Study of Chinese Stock Market

Author

Listed:
  • Jian Huang

    (Division of Business Management, Beijing Normal University-HongKong Baptist University United International College, Zhuhai 519087, China)

  • Huazhang Liu

    (Division of Business Management, Beijing Normal University-HongKong Baptist University United International College, Zhuhai 519087, China)

Abstract

To search significant variables which can illustrate the abnormal return of stock price, this research is generally based on the Fama-French five-factor model to develop a multi-factor model. We evaluated the existing factors in the empirical study of Chinese stock market and examined for new factors to extend the model by OLS and ridge regression model. With data from 2007 to 2018, the regression analysis was conducted on 1097 stocks separately in the market with computer simulation based on Python. Moreover, we conducted research on factor cyclical pattern via chi-square test and developed a corresponding trading strategy with trend analysis. For the results, we found that except market risk premium, each industry corresponds differently to the rest of six risk factors. The factor cyclical pattern can be used to predict the direction of seven risk factors and a simple moving average approach based on the relationships between risk factors and each industry was conducted in back-test which suggested that SMB (size premium), CMA (investment growth premium), CRMHL (momentum premium), and AMLH (asset turnover premium) can gain positive return.

Suggested Citation

  • Jian Huang & Huazhang Liu, 2019. "Examination and Modification of Multi-Factor Model in Explaining Stock Excess Return with Hybrid Approach in Empirical Study of Chinese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-30, May.
  • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:2:p:91-:d:234295
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    References listed on IDEAS

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    1. Arnab Bhattacharjee & Sudipto Roy, 2019. "Abnormal Returns or Mismeasured Risk? Network Effects and Risk Spillover in Stock Returns," JRFM, MDPI, vol. 12(2), pages 1-13, March.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. Aharoni, Gil & Grundy, Bruce & Zeng, Qi, 2013. "Stock returns and the Miller Modigliani valuation formula: Revisiting the Fama French analysis," Journal of Financial Economics, Elsevier, vol. 110(2), pages 347-357.
    4. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    5. Fama, Eugene F., 1996. "Multifactor Portfolio Efficiency and Multifactor Asset Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(4), pages 441-465, December.
    6. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    7. Nahida Akter & Ashadun Nobi, 2018. "Investigation of the Financial Stability of S&P 500 Using Realized Volatility and Stock Returns Distribution," JRFM, MDPI, vol. 11(2), pages 1-10, April.
    8. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    9. André Ricardo de Pinho Ronzani & Osvaldo Candido & Wilfredo Fernando Leiva Maldonado, 2017. "Goodness-of-Fit versus Significance: A CAPM Selection with Dynamic Betas Applied to the Brazilian Stock Market," IJFS, MDPI, vol. 5(4), pages 1-21, December.
    10. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    11. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    12. Zahedi, Javad & Rounaghi, Mohammad Mahdi, 2015. "Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 178-187.
    13. Jieting Chen & Yuichiro Kawaguchi, 2018. "Multi-Factor Asset-Pricing Models under Markov Regime Switches: Evidence from the Chinese Stock Market," IJFS, MDPI, vol. 6(2), pages 1-19, May.
    14. 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.
    15. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
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