Measuring currency exposure with quantile regression

Ding Du, Pin Ng, Xiaobing Zhao

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)549-566
Number of pages18
JournalReview of Quantitative Finance and Accounting
Volume41
Issue number3
DOIs
StatePublished - Oct 2013

Keywords

  • Currency exposure
  • Exposure puzzle
  • Missing variable bias
  • Quantile regression

ASJC Scopus subject areas

  • Accounting
  • General Business, Management and Accounting
  • Finance

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