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Real-Time Out-of-Sample Exchange Rate Predictability


  • Onur Ince
  • Tanya Molodtsova


This paper revisits the long-standing Meese and Rogoff puzzle by examining the importance of real-time data for exchange rate forecasting. Most of the existing literature on exchange rate predictability uses recent historical data, which are not available to the public at the time the forecasts are made. This paper evaluates short- and long-horizon out-of-sample exchange rate predictability using Purchasing Power Parity (PPP) and Taylor rule fundamentals for 16 OECD currencies during the post-Bretton Woods era. Comparing the results with real-time and revised data, the evidence of short-run exchange rate predictability with Taylor rule models is stronger with real-time data. The models with Taylor rule fundamentals outperform the naïve no-change model at the 1-quarter horizon for 8 out of 16 currencies vis-à-vis the U.S. dollar with real-time data and for 6 out of 16 currencies with revised data, with the strongest evidence coming from specifications that incorporate heterogeneous coefficients. The evidence of short-run predictability is much stronger with Taylor rule models than with conventional purchasing power parity model regardless of which type of data is used. The out-of-sample performance of both PPP and Taylor rule fundamentals improves at longer horizons, with PPP model performing best in the long run. At the 16-quarter horizon, the models with Taylor rule fundamentals outperform the random walk for 10 out of 16 currencies vis-à-vis the U.S. dollar with either type of data, while the PPP model outperforms the naïve no-change model for 13 out of 16 currencies with real-time data and for 11 out of 16 currencies with revised data. Key Words:

Suggested Citation

  • Onur Ince & Tanya Molodtsova, 2013. "Real-Time Out-of-Sample Exchange Rate Predictability," Working Papers 13-03, Department of Economics, Appalachian State University.
  • Handle: RePEc:apl:wpaper:13-03

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    References listed on IDEAS

    1. Corradi, Valentina & Fernandez, Andres & Swanson, Norman R., 2009. "Information in the Revision Process of Real-Time Datasets," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 455-467.
    2. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    3. Philippe Bacchetta & Eric van Wincoop, 2010. "Infrequent Portfolio Decisions: A Solution to the Forward Discount Puzzle," American Economic Review, American Economic Association, vol. 100(3), pages 870-904, June.
    4. Scholl, Almuth & Uhlig, Harald, 2008. "New evidence on the puzzles: Results from agnostic identification on monetary policy and exchange rates," Journal of International Economics, Elsevier, vol. 76(1), pages 1-13, September.
    5. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
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    Cited by:

    1. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations since the financial crisis: Performance evaluation and the role of monetary policy and safe haven," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 283-300.

    More about this item

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • F3 - International Economics - - International Finance

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