An application of returns-based style analysis to investigating the disappearance of the size premium

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1 Citation (Scopus)

Résumé

Purpose - The purpose of this study is to investigate explanations for the behaviour of the size premium using measures of large and small stock holdings of mutual funds. Design/methodology/approach - Returns-based style analysis is used to measure asset class exposure by regressing equity fund returns on asset class returns over the period 1965 to 2003. The coefficients estimate portfolio asset allocation indicating a fund's investment styles. The estimates from 36-month rolling regressions of US equity fund returns on various asset classes are aggregated and used as measures of investors' exposure to small stocks. The patterns are analyzed in the context of the behaviour of the abnormal returns to small stocks. Findings - The results indicate the importance of the 1974-1975 bear market to the historical size premium and support an overreaction and reversal argument. Exposure to small stocks drops dramatically between 1975 and 1977, suggesting a sell-off of small stocks. Fund exposure subsequently increases rapidly to its highest levels between 1982 and the market crash of 1987. These patterns are consistent with pricing pressure that would lead to the initial undervaluation and subsequent overvaluation driving returns to small stocks over this period. Originality/value - The study introduces the application of the returns-based style analysis methodology to studying an asset-pricing phenomenon and demonstrates important insights that can be obtained from the use of this methodology in new contexts and at an aggregate level.

Langue d'origineEnglish
Pages (de-à)216-234
Nombre de pages19
JournalJournal of Modelling in Management
Volume4
Numéro de publication3
DOI
Statut de publicationPublished - janv. 1 2009
Publié à l'externeOui

Note bibliographique

Publisher Copyright:
© 2009, © Emerald Group Publishing Limited.

ASJC Scopus Subject Areas

  • General Decision Sciences
  • Strategy and Management
  • Management Science and Operations Research

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