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The Forward Exchange Rate Unbiasedness Hypothesis: A Single Break Unit Root and CointegrationAnalysis

Author

Listed:
  • Michael Mazur
  • Miguel Ramirez

    () (Department of Economics, Trinity College)

Abstract

In an age of globalized finance, Forex market efficiency is particularly relevant as agents engage in arbitrage opportunities across international markets. This study tests the forward exchange rate unbiasedness hypothesis using more powerful tests such as the Zivot-Andrews single-break unit root and the KPSS stationarity (no unit root) tests to confirm that the USD/EUR spot and three-month forward rates are I(1) in nature. The study successfully employs Engle-Granger cointegration analysis which identifies a stable long-run relationship between the spot and forward rates and generates an ECM model that is used to forecast the in-sample (historical) data.The study’s findings refute past conclusions that fail to identify the data’s I(1) nature and suggests that market efficiency is present in the long run but not necessarily in the short run.

Suggested Citation

  • Michael Mazur & Miguel Ramirez, 2013. "The Forward Exchange Rate Unbiasedness Hypothesis: A Single Break Unit Root and CointegrationAnalysis," Working Papers 1310, Trinity College, Department of Economics.
  • Handle: RePEc:tri:wpaper:1310
    as

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    File URL: http://internet2.trincoll.edu/repec/WorkingPapers2013/WP13-10.pdf
    File Function: First version, 2013
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    More about this item

    Keywords

    Cointegration analysis; Error-correction model (ECM); Forward exchange rate unbiasedness hypothesis (FRUH); KPSS no unit root test; unexploited profits; and Zivot-Andrews single break unit root test;

    JEL classification:

    • F3 - International Economics - - International Finance
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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