[In Press] Expected idiosyncratic entropy

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose - We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Design/methodology/approach - We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy. Findings - We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns. Originality/value - We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.
Original languageEnglish
Number of pages33
JournalChina Accounting and Finance Review
Publication statusPublished - 2024

Open Access - Access Right Statement

© Mohammadreza Tavakoli Baghdadabad. Published in China Accounting and Finance Review. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Fingerprint

Dive into the research topics of '[In Press] Expected idiosyncratic entropy'. Together they form a unique fingerprint.

Cite this