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Portfolio Choice: Familiarity, Hedging, and Industry Bias

Published online by Cambridge University Press:  07 September 2020

Xin Che*
Affiliation:
California State University, Fullerton Mihaylo College of Business and Economics
Andre P. Liebenberg
Affiliation:
University of Mississippi School of Business [email protected]
Andrew A. Lynch
Affiliation:
University of Arkansas Walton College of [email protected]
*
[email protected] (corresponding author)

Abstract

Investors may underdiversify their portfolios by overweighting securities in which they perceive an informational advantage or by underweighting securities to hedge risks outside the portfolio. We investigate underdiversification in institutional portfolio construction by examining the under/overweighting of industries in U.S. property–liability (PL) insurers’ equity portfolios. We find that PL insurers underweight both their own industry and highly correlated industries in their portfolios. This underweighting is larger for PL insurers exposed to higher underwriting risk. Although PL insurers have an informational advantage in investing in their peers, their underwriting risk drives them to underweight stocks in their industry.

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

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Footnotes

We appreciate helpful comments from Thomas Berry-Stölzle, Hendrik Bessembinder (the editor), Mary Kelly, Young Park, Andy Puckett, and Andrei Simonov (the referee). We are also thankful for comments from conference participants at the 2017 Southern Risk and Insurance Association, 2018 Financial Management Association, 2018 American Risk and Insurance Association, 2019 Western Risk and Insurance Association, and 2020 Southwestern Finance Association annual meetings, and seminar participants at California State University Fullerton, Florida State University, James Madison University, John Carroll University, Peking University, and University of Tulsa.

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