Campus Units

Economics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2013

Journal or Book Title

Journal of Banking & Finance

Volume

37

Issue

8

First Page or Article ID Number

3064

Last Page

6075

DOI

10.1016/j.jbankfin.2013.02.034

Abstract

This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000–2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.

Comments

NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Banking & Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking & Finance, [37, 8, (2013)] DOI:10.1016/j.jbankfin.2013.02.034

Rights

This is an open access article distributed under the Creative Commons No Derivatives License, which permits unrestricted use and distribution, provided the original work is properly cited.

Copyright Owner

Elsevier Ltd.

Language

en

File Format

application/pdf

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