Document Type

Article

Publication Date

2012

Publication Title

Open Economies Review

Volume

23

Issue

2

Pages

337-357

Abstract

We perform non-linearity tests using daily data for leading currencies that include the Australian dollar, British pound, Brazilian real, Canadian dollar, euro, Japanese yen, Mexican peso, and the Swiss franc to resolve the issue of whether these currencies are driven by fundamentals or exogenous shocks to the global economy. In particular, we use a new method of testing for linear and nonlinear lead/lag relationships between time series, introduced by Brooks and Hinich (1999), based on the concepts of cross-correlation and crossbicorrelation. Our evidence points to a relatively rare episodic nonlinearity within and across foreign exchange rates. We also test the validity of specifying ARCH-type error structures for foreign exchange rates. In doing so, we estimate Bollerslevs (1986) generalized ARCH (GARCH) model and Nelsons (1988) exponential GARCH (EGARCH) model, using a variety of error densities [including the normal, the Student-t distribution, and the Generalized Error Distribution (GED)] and a comprehensive set of diagnostic checks. We apply the Brooks and Hinich (1999) nonlinearity test to the standardized residuals of the optimal GARCH/EGARCH model for each exchange rate series and show that the nonlinearity in the exchange rates is not due to ARCH-type e⁄ects. This result has important implications for the interpretation of the recent voluminous literature which attempts to model nancial asset returns using this family of models.

Comments

Author Posting. © Springer International Publishing AG 2012. This is the authors' version of the work. It is posted here by permission of the Open Economies Review for personal use, not for redistribution, The definitive version was published in the Open Economies Review, vol. 23, no. 2, 2012, https://link.springer.com/article/10.1007%2Fs11079-010-9194-9

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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