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Risk-return trade-off, information diffusion, and U.S. stock market predictability

Author

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  • Haibin Xie

    (School of Banking and Finance, University of International Business and Economics, Beijing 100029, P. R. China)

  • Shouyang Wang

    (#x2020;Academy of Mathematics and Systems Science, Academy of Sciences, Beijing 100190, P. R. China)

Abstract

Recent academic literature in finance documents both risk-return trade-off and gradual information diffusion (ID). Motivated by these two financial theories, this paper proposes the ARCH-M model augmented by an ID indicator to forecast the U.S. stock market returns. Empirical studies performed on the monthly S&P500 index show that our approach is useful in both statistical and economic sense. Further analysis shows that the ID provides complementary information to risk-return trade-off effect. Our findings confirm that financial theories are valuable for stock return forecasting.

Suggested Citation

  • Haibin Xie & Shouyang Wang, 2015. "Risk-return trade-off, information diffusion, and U.S. stock market predictability," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-20, December.
  • Handle: RePEc:wsi:ijfexx:v:02:y:2015:i:04:n:s2424786315500383
    DOI: 10.1142/S2424786315500383
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    Cited by:

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    2. Sarat Chandra Nayak & Bijan Bihari Misra, 2018. "Estimating stock closing indices using a GA-weighted condensed polynomial neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-22, December.
    3. Qiao, Kenan & Ji, Zhehan & Xie, Haibin, 2023. "Unrealized return dispersion and the equity risk premium," Finance Research Letters, Elsevier, vol. 58(PA).

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