Cross-Sectional Dispersion of Risk in Trading Time

T. Andersen, Martin Thyrsgaard, V. Todorov
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引用次数: 1

Abstract

We study the temporal behavior of the cross-sectional distribution of assets' market exposure, or betas, using a large panel of high-frequency returns. The asymptotic setup has the sampling frequency of the returns increasing to infinity, while the time span of the data remains fixed, and the cross-sectional dimension is fixed or increasing. We derive a Central Limit Theorem (CLT) for the cross-sectional beta dispersion at a point in time, enabling us to test whether this quantity varies across the trading day. We further derive a functional CLT for the dispersion statistics, allowing us to test if the beta dispersion, as a function of time-of-day, changes across days. We extend this further by developing inference techniques for the entire cross-sectional beta distribution at fixed points in time. We demonstrate, for constituents of the S&P 500 index, that the beta dispersion is elevated at the market open, gradually declines over the trading day, and is less than half the original value by the market close. The intraday beta dispersion pattern also changes over time and evolves differently on macroeconomic announcement days. Importantly, we find that the intraday variation in market betas is a source of priced risk.
交易时间内风险的横截面分散
我们研究了资产市场敞口的横截面分布的时间行为,或贝塔,使用一个大的高频回报面板。在渐近设置中,回归的采样频率增加到无穷大,而数据的时间跨度保持固定,截面维固定或增加。我们导出了一个中心极限定理(CLT)的横截面贝塔分散在一个时间点,使我们能够测试这个数量是否在交易日变化。我们进一步推导了离散统计的功能CLT,允许我们测试β离散是否作为一天中时间的函数在几天内发生变化。我们通过开发在固定时间点的整个横截面beta分布的推理技术进一步扩展了这一点。我们证明,对于标准普尔500指数的组成部分,beta分散度在市场开盘时升高,在交易日中逐渐下降,并且在市场收盘时不到原始价值的一半。日内beta分散模式也会随着时间的推移而变化,在宏观经济公告日的演变也会有所不同。重要的是,我们发现市场贝塔系数的日内变动是定价风险的一个来源。
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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