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Robust Tests of Forward Exchange Market Efficiency with Empirical Evidence from the 1920s

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  • Phillips, Peter C B
  • McFarland, James W
  • McMahon, Patrick C

Abstract

This paper provides a robust statistical approach to testing the unbiasedness hypothesis in forward exchange market efficiency studies. The methods we use allow us to work explicitly with levels rather than differenced data. They are statistically robust to data distributions with heavy tails, and they can be applied to data sets where the frequency of observation and the futures maturity do not coincide. In addition, our methods allow for stochastic trend nonstationarity and general forms of serial dependence. The methods are applied to daily data of spot exchange rates and forward exchange rates during the 1920's, which marked the first episode of a broadly general floating exchange rate system. The tail behavior of the data is analyzed using an adaptive data-based method for estimating the tail slope of the density. The results confirm the need for the use of robust regression methods. We find cointegration between the forward rate and spot rate for the four currencies we consider (the Belgian and French francs, the Italian lira and the US dollar, all measured against the British pound), we find support for a stationary risk premium in the case of the Belgian franc, the Italian lira and the US dollar, and we find support for the simple market efficiency hypothesis (where the forward rate is an unbiased predictor of the future spot rate and there is a zero mean risk premium) in the case of the US dollar.
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  • Phillips, Peter C B & McFarland, James W & McMahon, Patrick C, 1996. "Robust Tests of Forward Exchange Market Efficiency with Empirical Evidence from the 1920s," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 1-22, Jan.-Feb..
    • Handle: RePEc:jae:japmet:v:11:y:1996:i:1:p:1-22
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    23. Phillips, Peter C.B., 1995. "Robust Nonstationary Regression," Econometric Theory, Cambridge University Press, vol. 11(5), pages 912-951, October.
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    3. Choudhry, Taufiq, 1999. "Re-examining forward market efficiency Evidence from fractional and Harris-Inder cointegration tests," International Review of Economics & Finance, Elsevier, vol. 8(4), pages 433-453, November.
    4. Phillips, Peter C. B. & McFarland, James W., 1997. "Forward exchange market unbiasedness: the case of the Australian dollar since 1984," Journal of International Money and Finance, Elsevier, vol. 16(6), pages 885-907, December.
    5. Richard T. Baillie & Young Wook Han, 2019. "Long Memory Volatility, Central Bank Intervention and Uncovered Interest Rate Parity in the 1920s Exchange Markets," Korean Economic Review, Korean Economic Association, vol. 35, pages 183-203.
    6. R.D. Rossiter, 2002. "Term structure of forward exchange premiums: evidence from the 1920s," Journal of Economic Studies, Emerald Group Publishing, vol. 29(1), pages 33-47, January.
    7. Alex Maynard, 2003. "Testing for Forward-Rate Unbiasedness: On Regression in Levels and in Returns," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 313-327, May.
    8. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing Forward Exchange Rate Unbiasedness Efficiently: A Semiparametric Approach," Journal of Applied Economics, Taylor & Francis Journals, vol. 7(1), pages 325-353, May.
    9. Scott Barnhart & Robert McNown & Myles Wallace, 2002. "Some answers to puzzles in testing unbiasedness in the foreign exchange market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 687-696.
    10. Cotter, John, 2001. "Margin exceedences for European stock index futures using extreme value theory," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1475-1502, August.
    11. Ho, Tsung-Wu, 2003. "A re-examination of the unbiasedness forward rate hypothesis using dynamic SUR model," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 542-559.
    12. Gallagher, Liam A. & Taylor, Mark P., 2000. "Measuring the temporary component of stock prices: robust multivariate analysis," Economics Letters, Elsevier, vol. 67(2), pages 193-200, May.
    13. D. M. Mahinda Samarakoon & Keith Knight, 2009. "A Note on Unit Root Tests with Infinite Variance Noise," Econometric Reviews, Taylor & Francis Journals, vol. 28(4), pages 314-334.
    14. Accominotti, Olivier & Chambers, David, 2014. "Out-of-sample evidence on the returns to currency trading," Economic History Working Papers 84582, London School of Economics and Political Science, Department of Economic History.
    15. John Cotter, 2005. "Tail behaviour of the euro," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 827-840.
    16. Serttas, Fatma Ozgu, 2010. "Essays on infinite-variance stable errors and robust estimation procedures," ISU General Staff Papers 201001010800002742, Iowa State University, Department of Economics.
    17. Frezza, Massimiliano, 2012. "Modeling the time-changing dependence in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(12), pages 1510-1520.
    18. Hodgson, Douglas J., 1998. "Adaptive estimation of cointegrating regressions with ARMA errors," Journal of Econometrics, Elsevier, vol. 85(2), pages 231-267, August.
    19. Nucci, Francesco, 2003. "Cross-currency, cross-maturity forward exchange premiums as predictors of spot rate changes: Theory and evidence," Journal of Banking & Finance, Elsevier, vol. 27(2), pages 183-200, February.
    20. Jorge Andrés Muñoz Mendoza & Carmen Lissette Veloso Ramos & Sandra María Sepúlveda Yelpo & Carlos Leandro Delgado Fuentealba & Edinson Edgardo Cornejo Saavedra, 2022. "Exchange Markets and Stock Markets Integration in Latin-America," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(3), pages 1-24, Julio - S.
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