Assessing the idiosyncratic risk and stock returns relation in heteroskedasticity corrected predictive models using quantile regression

Harmindar B Nath, Robert Darren Brooks

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)


This paper examines the superiority-claim of the GARCH based measure in resolving the idiosyncratic risk-return puzzle using Australian data. The least squares and the quantile regressions of stock-returns on lagged idiosyncratic-volatility estimated from daily data using two measures (including GARCH) fail to support such claim. The quantile regression estimation reveals the risk-return relationship to be quantile dependent; it is parabolic but significant only at the extreme quantiles. The parabolic-form is convex (concave) at the lower (upper) quantiles of the returns conditional distribution. This changing relationship-form reflects uncertainty in predicting returns. Moreover, the idiosyncratic risk-return puzzle is a model specification problem.
Original languageEnglish
Pages (from-to)94 - 111
Number of pages18
JournalInternational Review of Economics and Finance
Publication statusPublished - 2015

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