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Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method

Author

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  • Zhifeng Dai

    (College of Mathematics and Statistics, Changsha University of Science and Technology, Changsha 410114, Hunan, China)

  • Huiting Zhou

    (College of Mathematics and Statistics, Changsha University of Science and Technology, Changsha 410114, Hunan, China)

Abstract

Forecasting stock market returns has great significance to asset allocation, risk management, and asset pricing, but stock return prediction is notoriously difficult. In this paper, we combine the sum-of-the-parts (SOP) method and three kinds of economic constraint methods: non-negative economic constraint strategy, momentum of return prediction strategy, and three-sigma strategy to improve prediction performance of stock returns, in which the price-earnings ratio growth rate ( gm ) is predicted by economic constraint methods. Empirical results suggest that the stock return forecasts by proposed models are both statistically and economically significant. The predictions of proposed models are robust to various robustness tests.

Suggested Citation

  • Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:541-:d:307513
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    References listed on IDEAS

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    4. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
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