Quantile regression: its application in investment analysis

D.E. Allen, Paul Gerrans, A.K. Singh, R. Powell

Research output: Contribution to journalArticlepeer-review

17 Citations (Web of Science)

Abstract

Quantile regression is a very powerful tool for financial research and risk modelling, and we believe that it has further applications that can provide significant insights in empirical work in finance. This paper demonstrates its use on a sample of Australian stocks and shows that, while ordinary least squares regression is not effective in capturing the extreme values or the adverse losses evident in return distributions, these are captured by quantile regressions.(1)
Original languageEnglish
Pages (from-to)7-12
JournalJASSA-THE FINSIA JOURNAL OF APPLIED FINANCE
Volume1
Issue number4
Publication statusPublished - 2009

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