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Markov switching and exchange rate predictability

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  • Nikolsko-Rzhevskyy, Alex
  • Prodan, Ruxandra

Abstract

We first show that the recent success of modern macroeconomic models in forecasting nominal exchange rates, evaluated using the Clark and West (2006) inference procedure, is partly due to the presence of the constant term (drift), in addition to the economic fundamentals. We then model the drift term using the two-state Markov switching stochastic segmented trend model and present evidence of both short-run (one month) and long-run (up to one year) predictability for monthly exchange rates over the post-Bretton Woods period. This is an important result, as the recent literature has typically failed to find evidence of consistent multi-horizon predictability. The model strongly outperforms the random walk for 9 out of 12 exchange rate series at short horizons; for 7 of the 12 exchange rates, we find evidence of a long-run predictability that declines as the forecast horizon increases. Our results remain robust to alternative test statistics and forecast windows.

Suggested Citation

  • Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
  • Handle: RePEc:eee:intfor:v:28:y:2012:i:2:p:353-365
    DOI: 10.1016/j.ijforecast.2011.04.007
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    References listed on IDEAS

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    Cited by:

    1. Slim Chaouachi & Zied Ftiti & Frederic Teulon, 2014. "Explaining the Tunisian Real Exchange: Long Memory versus Structural Breaks," Working Papers 2014-147, Department of Research, Ipag Business School.
    2. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    3. repec:trp:01jefa:jefa0003 is not listed on IDEAS
    4. Harris, Richard D. F. & Nguyen, Linh H & Stoja, Evarist, 2015. "Extreme downside risk and financial crises," Bank of England working papers 547, Bank of England.
    5. Levent Bulut, 2017. "Does Statistical Significance Help to Evaluate Predictive Performance of Competing Models?," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 1(1), pages 1-13.
    6. Panagiotis Papaioannnou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Papers 1310.5306, arXiv.org.
    7. repec:ipg:wpaper:2014-390 is not listed on IDEAS
    8. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.

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