The Journal of Finance Volume 71, Issue 6, December 2016 ,Pages 2967–3006

罕见再平衡👵🏿，收益自相关和季节性

作者：Vincent Bogousslavsky (Ecole Polytechnique Fédérale de Lausanne)

摘要：一个罕见的再平衡模型可以解释在时间序列和横截面股票收益率中的特定预测类型。首先，罕见的再平衡可以产生收益的自相关性🙍🏻，这和来自日内收益率的实证证据以及日间收益率的新证据是一致的。自相关性可以转变符号，并且在再平衡模型中变成正的。其次，当更多的交易者进行再平衡时，期望收益率的横截面方差会变得更大。这个影响产生了股票收益率的季节性🧜🏼‍♀️，从而帮助解释已有的实证证据🌂。

Infrequent Rebalancing, Return Autocorrelation, and Seasonality

Vincent Bogousslavsky (Ecole Polytechnique Fédérale de Lausanne)

ABSTRACT

A model of infrequent rebalancing can explain specific predictability patterns in the time series and cross-section of stock returns. First, infrequent rebalancing produces return autocorrelations that are consistent with empirical evidence from intraday returns and new evidence from daily returns. Autocorrelations can switch sign and become positive at the rebalancing horizon. Second, the cross-sectional variance in expected returns is larger when more traders rebalance. This effect generates seasonality in the cross-section of stock returns, which can help explain available empirical evidence.

原文链接: http://onlinelibrary.wiley.com/doi/10.1111/jofi.12436/full

翻译🌟：阙江静