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A New Test forMarket Efficiency and Uncovered Interest Parity

Author

Listed:
  • Richard T. Baillie

    (Michigan State University and University of London)

  • Francis X. Diebold

    (University of Pennsylvania)

  • George Kapetanios

    (University of London)

  • Kun Ho Kim

    (Concordia University)

Abstract
We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parameter estimates, and is not dependent on assumptions of strict exogeneity. This new approach is asymptotically more efficient than the common approach of using OLS withHAC robust standard errors in the static forward premium regression. The coefficient estimates when spot return changes are regressed on the forward premium are all positive and remarkably stable across currencies. These estimates are considerably larger than those of previous studies, which frequently find negative coefficients. The method also has the advantage of showing dynamic effects of risk premia, or other events that may lead to rejection of UIP or the efficient markets hypothesis.

Suggested Citation

  • Richard T. Baillie & Francis X. Diebold & George Kapetanios & Kun Ho Kim, 2022. "A New Test forMarket Efficiency and Uncovered Interest Parity," PIER Working Paper Archive 22-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Handle: RePEc:pen:papers:22-029
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    References listed on IDEAS

    as
    1. Richard T. Baillie & Francis X. Diebold & George Kapetanios & Kun Ho Kim, 2022. "On Robust Inference in Time Series Regression," PIER Working Paper Archive 22-012, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-853, October.
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    9. Frenkel, Jacob A, 1977. "The Forward Exchange Rate, Expectations, and the Demand for Money: The German Hyperinflation," American Economic Review, American Economic Association, vol. 67(4), pages 653-670, September.
    10. Baillie, Richard T & Lippens, Robert E & McMahon, Patrick C, 1983. "Testing Rational Expectations and Efficiency in the Foreign Exchange Market," Econometrica, Econometric Society, vol. 51(3), pages 553-563, May.
    11. Bilson, John F O, 1981. "The "Speculative Efficiency" Hypothesis," The Journal of Business, University of Chicago Press, vol. 54(3), pages 435-451, July.
    12. Lars Peter Hansen & Robert J. Hodrick, 1983. "Risk Averse Speculation in the Forward Foreign Exchange Market: An Econometric Analysis of Linear Models," NBER Chapters, in: Exchange Rates and International Macroeconomics, pages 113-152, National Bureau of Economic Research, Inc.
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    14. Levy, E & Nobay, A R, 1986. "The Speculative Efficiency Hypothesis: A Bivariate Analysis," Economic Journal, Royal Economic Society, vol. 96(380a), pages 109-121, Supplemen.
    15. Baillie, Richard T. & P. Osterberg, William, 1997. "Central bank intervention and risk in the forward market," Journal of International Economics, Elsevier, vol. 43(3-4), pages 483-497, November.
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    17. Baillie, Richard T. & Kilic, Rehim, 2006. "Do asymmetric and nonlinear adjustments explain the forward premium anomaly?," Journal of International Money and Finance, Elsevier, vol. 25(1), pages 22-47, February.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Dynamic regressions; forward premium anomaly; rational expectations; efficient markets; robust standard errors;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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