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

Harmindar B. Nath and Robert D. Brooks

International Review of Economics & Finance, 2015, vol. 38, issue C, 94-111

Abstract: 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.

Keywords: Idiosyncratic risk; Quantile regression; GARCH model; Panel data (search for similar items in EconPapers)
JEL-codes: C14 C21 C22 C23 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1016/j.iref.2014.12.012

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