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Testing forward exchange rate unbiasedness efficiently: a semiparametric approach

We apply semiparametric efficient estimation procedures for a seemingly unrelated regression model where the multivariate error density is elliptically symmetric to study the efficiency of the foreign exchange market. We consider both cointegrating regressions and standard stationary regressions. The elliptical symmetry assumption allows us to avoid the curse of dimensionality problem that typically arises in multivariate semiparametric estimation procedures, because the multivariate elliptically symmetric density function can be written as a function of a scalar transformation of the observed multivariate data. We test the unbiasedness hypothesis on both weekly and daily exchange rate data and strongly reject unbiasedness at the weekly horizon, but fail to reject the unbiasedness hypothesis on the daily data. Estimates of the semiparametric procedure in some cases differ substantially from traditional OLS estimates.

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Article provided by Universidad del CEMA in its journal Journal of Applied Economics.

Volume (Year): VII (2004)
Issue (Month): (November)
Pages: 325-353

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Handle: RePEc:cem:jaecon:v:7:y:2004:n:2:p:325-353
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  1. Peter C.B. Phillips, 1993. "Robust Nonstationary Regression," Cowles Foundation Discussion Papers 1064, Cowles Foundation for Research in Economics, Yale University.
  2. Oliver Linton & Douglas J.Hodgson & Keith Vorkink, 2001. "Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach," FMG Discussion Papers dp382, Financial Markets Group.
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  17. Cornell, Bradford, 1989. "The impact of data errors on measurement of the foreign exchange risk premium," Journal of International Money and Finance, Elsevier, vol. 8(1), pages 147-157, March.
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