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Identifying Exchange Rate Common Factors

Author

Listed:
  • Ryan Greenaway-McGrevy
  • Donggyu Sul
  • Nelson Mark
  • Jyh-Lin Wu

Abstract

Using recently developed model selection procedures, we determine that exchange rate returns are driven by a two-factor model. We identify them as a dollar factor and a euro factor. Exchange rates are thus driven by global, US, and Euro-zone stochastic discount factors. The identified factors can also be given a risk-based interpretation. Identification motivates multilateral models for bilateral exchange rates. Out-of-sample forecast accuracy of empirically identified multilateral models dominate the random walk and a bilateral purchasing power parity fundamentals prediction model. 24-month ahead forecast accuracy of the multilateral model dominates those of a principal components forecasting model.

Suggested Citation

  • Ryan Greenaway-McGrevy & Donggyu Sul & Nelson Mark & Jyh-Lin Wu, 2017. "Identifying Exchange Rate Common Factors," NBER Working Papers 23726, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:23726
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    References listed on IDEAS

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    1. Hassan, Tarek & Mano, Rui C., 2014. "Forward and Spot Exchange Rates in a Multi-currency World," CEPR Discussion Papers 10060, C.E.P.R. Discussion Papers.
    2. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "A panel project on purchasing power parity: Mean reversion within and between countries," Journal of International Economics, Elsevier, vol. 40(1-2), pages 209-224, February.
    3. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    4. Groen, Jan J J, 2005. "Exchange Rate Predictability and Monetary Fundamentals in a Small Multi-country Panel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 495-516, June.
    5. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    6. Hanno Lustig & Robert J. Richmond, 2017. "Gravity in FX R-Squared: Understanding the Factor Structure in Exchange Rates," NBER Working Papers 23773, National Bureau of Economic Research, Inc.
    7. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    8. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    9. Mark, Nelson C. & Sul, Donggyu, 2001. "Nominal exchange rates and monetary fundamentals: Evidence from a small post-Bretton woods panel," Journal of International Economics, Elsevier, vol. 53(1), pages 29-52, February.
    10. Berg, Kimberly A. & Mark, Nelson C., 2015. "Third-country effects on the exchange rate," Journal of International Economics, Elsevier, vol. 96(2), pages 227-243.
    11. Rapach, David E. & Wohar, Mark E., 2004. "Testing the monetary model of exchange rate determination: a closer look at panels," Journal of International Money and Finance, Elsevier, vol. 23(6), pages 867-895, October.
    12. Jason Parker & Donggyu Sul, 2016. "Identification of Unknown Common Factors: Leaders and Followers," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 227-239, April.
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    Cited by:

    1. HORIE, Tetsushi & YAMAMOTO, Yohei, 2016. "Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets," Discussion Papers 2016-04, Graduate School of Economics, Hitotsubashi University.
    2. Shuo Cao & Hongyi Chen, 2017. "Exchange Rate Movements and Fundamentals: Impact of Oil Prices and China¡¯s Growth," Working Papers 042017, Hong Kong Institute for Monetary Research.
    3. Pierre Guerin & Danilo Leiva-Leon & Massimiliano Marcellino, 2016. "Markov-Switching Three-Pass Regression Filter," Working Papers 591, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    More about this item

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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