散户投资者的交易活动与股票收益相关性的可预测性

Daniele Ballinari
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引用次数: 0

摘要

大量的理论和实证证据将价格变动与散户投资者的行为联系起来。然而,在预测股票收益相关性时,研究主要集中在杠杆效应上。我们提出了一种新的实现协方差模型,允许外生预测因子影响相关动态,同时确保预测矩阵的正确定性。利用该模型,分析了散户情绪和注意力对35只道琼斯股票相关性的预测能力。我们发现,散户投资者的注意力对回报相关性具有预测能力,尤其是在较长的预测期限和2019冠状病毒病大流行期间。风险价值预测证实了这些结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Retail Investors’ Trading Activity and the Predictability of Stock Return Correlations
Considerable theoretical and empirical evidence links price comovements with the behavior of retail investors. Nevertheless, when predicting stock return correlations, research has focused on the leverage effect. We propose a new model of realized covariances that allows exogenous predictors to influence the correlation dynamics while ensuring the predicted matrices' positive definiteness. Using this model, the predictive power of retail investors' sentiment and attention for the correlations of 35 Dow Jones stocks is analyzed. We find retail investors' attention to have predictive power for return correlations, especially for longer forecasting horizons and during the COVID-19 pandemic. Value-at-risk forecasts confirm these results.
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