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Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?

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  • Zhifeng Dai
  • Xiaoming Chang

Abstract

We find that imposing economic constraint on stock return forecasts based on the Interquartile Range of equity premium can significantly strengthen predictive performance. Specifically, we construct a judgment mechanism that truncates the outliers in forecasts of stock return. We prove that our constraint approach can realize more accurate predictive information relative to the unconstraint approach from the perspective of statistics and economics. In addition, the new constraint approach can effectively defeat CT constraint and CDA strategy. The three mixed models we proposed can further enhance the accuracy of prediction, especially the mixed model combined with our constraint approach. Finally, utilizing our new constraint approach can help investors obtain considerable economic gains. With the application of extension and robustness analysis, our results are robust.

Suggested Citation

  • Zhifeng Dai & Xiaoming Chang, 2021. "Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, June.
    • Handle: RePEc:hin:jnlmpe:9911986
    DOI: 10.1155/2021/9911986
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    Cited by:

    1. Kejin Wu & Sayar Karmakar, 2023. "A model-free approach to do long-term volatility forecasting and its variants," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    2. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2022. "Ghostbusters: Hunting abnormal flights in Europe during COVID-19," Transport Policy, Elsevier, vol. 127(C), pages 203-217.

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