Measuring currency exposure with quantile regression

Ding Du, Pin Ng () and Xiaobing Zhao ()

Review of Quantitative Finance and Accounting, 2013, vol. 41, issue 3, 549-566

Abstract: In this paper, we explore an alternative explanation of the exposure puzzle, the missing variable bias in previous studies. We propose to correct the bias with the quantile regression technique invented by Koenker and Bassett (Econometrica 46:33–51, 1978 ). Empirically, as soon as we take into account the missing variable bias as well as time variation in currency exposure, we find that 26 out of 30 or 87 % of the US industry portfolios exhibit significant currency exposure to the Major Currencies Index, and 23 out of 30 or 77 % show significant exposure to the Other Important Trading Partners Index. Our results have important theoretical and practical implications. In terms of theoretical significance, our results strengthen the findings in Francis et al. (J Financ Econ 90:169–196, 2008 ), and suggest that methodological weakness, not hedging, may explain the insignificance of currency risk in previous studies. In terms of practical significance, our results suggest a simple yet efficient approach for managers to estimate currency exposure of their firms. Copyright Springer Science+Business Media New York 2013

Keywords: Currency exposure; Missing variable bias; Exposure puzzle; Quantile regression; G15; F31 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11156-012-0322-z

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