Cross-Section of Equity Returns: Stock Market Volatility and Priced Factors

Bumjean Sohn
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引用次数: 9

Abstract

We discuss the nature of risk valid factors should represent. The Campbell's (1993) ICAPM extended with heteroskedastic asset returns guides us to identify the risk; we show that many of empirically well-established factors contain information about the future changes in the investment opportunity set and that is why these factors are strongly priced across assets. Specifically, we show that size, momentum, liquidity (trading strategy based factors), industrial production growth, and inflation (macroeconomic factors) factors as well as both short- and long-run market volatility factors are significantly priced because they all have information about the changes in the future market volatility which characterizes the future investment opportunity set in our model. The time-series studies show that the above-mentioned factors do predict the market volatility and the cross-sectional studies show that these factors are priced due to their predictability on the future market volatility. Both studies are consistent and strongly support the relationship between the stock market volatility and the priced factors. By revealing the nature of risk the empirically well-established factors represent, we provide an explanation why we observe so many empirically strong factors in the literature.
股票收益横截面:股票市场波动和定价因素
我们讨论了风险的性质,有效因素应该代表。Campbell(1993)用异方差资产回报扩展的ICAPM指导我们识别风险;我们表明,许多经过实证验证的因素包含有关投资机会集未来变化的信息,这就是为什么这些因素在资产中被强烈定价的原因。具体来说,我们表明规模、动量、流动性(基于交易策略的因素)、工业生产增长和通货膨胀(宏观经济因素)因素以及短期和长期市场波动因素都是显著定价的,因为它们都有关于未来市场波动变化的信息,而未来市场波动是我们模型中设定的未来投资机会的特征。时间序列研究表明上述因素确实预测了市场波动,横断面研究表明这些因素由于其对未来市场波动的可预测性而被定价。两项研究结果一致,有力地支持了股票市场波动与定价因素之间的关系。通过揭示风险的本质,经验完善的因素代表,我们提供了一个解释,为什么我们观察到这么多的经验强有力的因素在文献中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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