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Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?
Mathematical Problems in Engineering ( IF 1.430 ) Pub Date : 2021-06-21 , DOI: 10.1155/2021/9911986 Zhifeng Dai 1 , Xiaoming Chang 1
Mathematical Problems in Engineering ( IF 1.430 ) Pub Date : 2021-06-21 , DOI: 10.1155/2021/9911986 Zhifeng Dai 1 , Xiaoming Chang 1
Affiliation
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.
中文翻译:
用经济约束预测股票回报:四分位距能否截断异常值?
我们发现,基于股权溢价的四分位区间对股票收益预测施加经济约束可以显着增强预测性能。具体来说,我们构建了一个判断机制,在股票收益预测中截断异常值。我们证明,从统计学和经济学的角度来看,我们的约束方法相对于无约束方法可以实现更准确的预测信息。此外,新的约束方法可以有效地击败 CT 约束和 CDA 策略。我们提出的三种混合模型可以进一步提高预测的准确性,尤其是结合我们的约束方法的混合模型。最后,利用我们新的约束方法可以帮助投资者获得可观的经济收益。随着可拓性和稳健性分析的应用,
更新日期:2021-06-21
中文翻译:
用经济约束预测股票回报:四分位距能否截断异常值?
我们发现,基于股权溢价的四分位区间对股票收益预测施加经济约束可以显着增强预测性能。具体来说,我们构建了一个判断机制,在股票收益预测中截断异常值。我们证明,从统计学和经济学的角度来看,我们的约束方法相对于无约束方法可以实现更准确的预测信息。此外,新的约束方法可以有效地击败 CT 约束和 CDA 策略。我们提出的三种混合模型可以进一步提高预测的准确性,尤其是结合我们的约束方法的混合模型。最后,利用我们新的约束方法可以帮助投资者获得可观的经济收益。随着可拓性和稳健性分析的应用,