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

罕見再平衡，收益自相關和季節性

作者：Vincent Bogousslavsky (Ecole Polytechnique Fédérale de Lausanne)

摘要：一個罕見的再平衡模型可以解釋在時間序列和橫截面股票收益率中的特定預測類型。首先，罕見的再平衡可以産生收益的自相關性，這和來自日内收益率的實證證據以及日間收益率的新證據是一緻的。自相關性可以轉變符号，并且在再平衡模型中變成正的。其次，當更多的交易者進行再平衡時，期望收益率的橫截面方差會變得更大。這個影響産生了股票收益率的季節性，從而幫助解釋已有的實證證據。

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.

原文鍊接: http://onlinelibrary.wiley.com/doi/10.1111/jofi.12436/full

翻譯：阙江靜