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Taylor Rule Deviations and Out-of-Sample Exchange Rate Predictability

Author

Listed:
  • Onur Ince
  • Tanya Molodtsova
  • David H. Papell

Abstract

The Taylor rule has become the dominant model for academic evaluation of out-of-sample exchange rate predictability. Two versions of the Taylor rule model are the Taylor rule fundamentals model, where the variables that enter the Taylor rule are used to forecast exchange rate changes, and the Taylor rule differentials model, where a Taylor rule with postulated coefficients is used in the forecasting regression. We use data from 1973 to 2014 to evaluate short-run out-of-sample predictability for eight exchange rates vis-à-vis the U.S. dollar, and find strong evidence in favor of the Taylor rule fundamentals model alternative against the random walk null. The evidence of predictability is weaker with the Taylor rule differentials model, and still weaker with the traditional interest rate differential, purchasing power parity, and monetary models. The evidence of predictability for the fundamentals model is not related to deviations from the original Taylor rule for the U.S., but is related to deviations from a modified Taylor rule for the U.S. with a higher coefficient on the output gap. The evidence of predictability is also unrelated to deviations from Taylor rules for the foreign countries and adherence to the Taylor principle for the U.S. Key Words:

Suggested Citation

  • Onur Ince & Tanya Molodtsova & David H. Papell, 2015. "Taylor Rule Deviations and Out-of-Sample Exchange Rate Predictability," Working Papers 15-02, Department of Economics, Appalachian State University.
  • Handle: RePEc:apl:wpaper:15-02
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    Cited by:

    1. Salisu, Afees A. & Vo, Xuan Vinh, 2021. "The behavior of exchange rate and stock returns in high and low interest rate environments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 138-149.
    2. Teona Shugliashvili, 2023. "The words have power: the impact of news on exchange rates," FFA Working Papers 5.006, Prague University of Economics and Business, revised 31 Jul 2023.
    3. Michael Frenkel & Matthias Mauch & Jan-Christoph Rülke, 2017. "Forecaster Rationality and Expectation Formation in Foreign Exchange Markets: Do Emerging Markets Differ from Industrialized Economies?," WHU Working Paper Series - Economics Group 17-04, WHU - Otto Beisheim School of Management.
    4. David Alaminos & M. Belén Salas & Manuel Á. Fernández-Gámez, 2023. "Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-21, December.
    5. Jair N. Ojeda-Joya, 2014. "A Consumption-Based Approach to Exchange Rate Predictability," Borradores de Economia 12339, Banco de la Republica.
    6. Sarthak Behera & Hyeongwoo Kim, 2019. "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series auwp2019-04, Department of Economics, Auburn University.
    7. Beckmann, Joscha & Czudaj, Robert L., 2025. "Fundamental determinants of exchange rate expectations," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1003-1021.
    8. Christina Anderl & Guglielmo Maria Caporale, 2022. "Exchange rate parities and Taylor rule deviations," Empirical Economics, Springer, vol. 63(4), pages 1809-1835, October.
    9. Joseph Agyapong, 2021. "Application of Taylor Rule Fundamentals in Forecasting Exchange Rates," Economies, MDPI, vol. 9(2), pages 1-27, June.
    10. Darvas, Zsolt & Schepp, Zoltán, 2024. "Exchange rates and fundamentals: Forecasting with long maturity forward rates," Journal of International Money and Finance, Elsevier, vol. 143(C).
    11. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    12. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
    13. Lebogang Mateane & Christian R. Proaño, 2020. "Does monetary policy react asymmetrically to exchange rate misalignments? Evidence for South Africa," Empirical Economics, Springer, vol. 58(4), pages 1639-1658, April.
    14. Joscha Beckmann & Dionysius Glycopantis & Keith Pilbeam, 2018. "The dollar–euro exchange rate and monetary fundamentals," Empirical Economics, Springer, vol. 54(4), pages 1389-1410, June.
    15. Chen, Chuanglian & Yao, Shujie & Ou, Jinghua, 2017. "Exchange rate dynamics in a Taylor rule framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 158-173.
    16. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2020. "Predicting exchange rate returns," Emerging Markets Review, Elsevier, vol. 42(C).
    17. Chang, Ming-Jen & Matsuki, Takashi, 2022. "Exchange rate forecasting with real-time data: Evidence from Western offshoots," Research in International Business and Finance, Elsevier, vol. 59(C).

    More about this item

    JEL classification:

    • 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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