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Measuring currency exposure with quantile regression

Author

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  • Ding Du
  • Pin Ng
  • Xiaobing Zhao

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

Suggested Citation

  • Ding Du & Pin Ng & Xiaobing Zhao, 2013. "Measuring currency exposure with quantile regression," Review of Quantitative Finance and Accounting, Springer, vol. 41(3), pages 549-566, October.
  • Handle: RePEc:kap:rqfnac:v:41:y:2013:i:3:p:549-566
    DOI: 10.1007/s11156-012-0322-z
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    Cited by:

    1. Ding Du & Ronald J Gunderson & Xiaobing Zhao, 2016. "Investor sentiment and oil prices," Journal of Asset Management, Palgrave Macmillan, vol. 17(2), pages 73-88, March.
    2. Yi-hsun Lai & Wen-chang Lin & Liang-wei Kuo, 2018. "Forestalling capital regulation or masking financial weakness? Evidence from loss reserve management in the property–liability insurance industry," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 481-518, February.
    3. Suder, Gabriele & Liesch, Peter W. & Inomata, Satoshi & Mihailova, Irina & Meng, Bo, 2015. "The evolving geography of production hubs and regional value chains across East Asia: Trade in value-added," Journal of World Business, Elsevier, vol. 50(3), pages 404-416.
    4. Van Cauwenberge Annelies & Vancauteren Mark & Braekers Roel & Vandemaele Sigrid, 2022. "The degree of international trade and exchange rate exposure—Firm‐level evidence from two small open economies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3832-3850, October.
    5. Ding Du & Xiaobing Zhao, 2017. "Financial investor sentiment and the boom/bust in oil prices during 2003–2008," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 331-361, February.
    6. May Huaxi Zhang & Stanley Iat-Meng Ko & Andreas Karathanasopoulos & Chia Chun Lo, 2022. "A two-step quantile regression method for discretionary accounting," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 1-22, July.
    7. Ding Du, 2018. "The pricing of common exchange rate factors in the U.S. equity market," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 775-798, April.
    8. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2021. "Measuring and explaining firm-level exchange rate exposure: The role of foreign market destinations and international trade," Economic Modelling, Elsevier, vol. 105(C).
    9. Laura Ferrando & Román Ferrer & Francisco Jareño, 2017. "Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach," Manchester School, University of Manchester, vol. 85(2), pages 212-242, March.
    10. Yu-Yen Ku & Tze-Yu Yen, 2016. "Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-33, September.

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    More about this item

    Keywords

    Currency exposure; Missing variable bias; Exposure puzzle; Quantile regression; G15; F31;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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