Quantile regression: its application in investment analysis

David E. Allen, Paul Gerrans, Abhay Kumar Singh, Robert Powell

Research output: Contribution to journalArticleResearchpeer-review

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.
LanguageEnglish
Pages7-12
Number of pages6
JournalJASSA : the FINSIA journal of applied finance
Issue number4
Publication statusPublished - 2009
Externally publishedYes

Fingerprint

Quantile regression
Investment analysis
Finance
Extreme values
Return distribution

Keywords

  • capital markets
  • regression analysis
  • stock market

Cite this

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Quantile regression : its application in investment analysis. / Allen, David E.; Gerrans, Paul; Singh, Abhay Kumar; Powell, Robert.

In: JASSA : the FINSIA journal of applied finance, No. 4, 2009, p. 7-12.

Research output: Contribution to journalArticleResearchpeer-review

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