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首页> 外文会议>2007 China International Conference in Finance >Idiosyncratic Volatility and Skewness: Time Series Relations and the Cross-Section of Expected Returns
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Idiosyncratic Volatility and Skewness: Time Series Relations and the Cross-Section of Expected Returns

机译：特质波动率和偏度：时间序列关系和期望收益的横断面

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Investors with a preference for skewness may pay a premium for stocks with high idiosyncratic volatility because such stocks also offer high skewness. We find that lagged skewness alone is a weak predictor of expected skewness, and thus investors may rely on additional variables to forecast skewness. We estimate a model to forecast skewness and find that a number of variables suggested in the literature, especially idiosyncratic volatility, allow us to construct superior estimates of expected skewness. We find that controlling for expected skewness greatly reduces, both economically and statistically, the magnitude of the negative relationship between idiosyncratic volatility and expected returns.
机译：偏好偏度的投资者可能会为特异波动率高的股票支付溢价，因为此类股票也具有极高的偏度。我们发现，滞后偏斜度仅是预期偏斜度的弱预测指标，因此，投资者可能依赖于其他变量来预测偏斜度。我们估计了一个模型来预测偏度，发现文献中提出的许多变量，尤其是特异度波动性，使我们能够构建预期偏度的更好估计。我们发现，控制预期偏斜在经济和统计上都大大降低了特质波动率和预期收益之间的负关系。

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