Empirical Modeling of Exchange Rate Dynamics

1. Front Matter

   Pages N2-vii

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2. Introduction

   • Francis X. Diebold

   Pages 1-3

3. Conditional Heteroskedasticity in Economic Time Series

   • Francis X. Diebold

   Pages 4-32

4. Weekly Univariate Nominal Exchange Rate Fluctuations

   • Francis X. Diebold

   Pages 33-96

5. Monthly Univariate Nominal Exchange Rate Fluctuations

   • Francis X. Diebold

   Pages 97-111

6. Real Exchange Rate Movements

   • Francis X. Diebold

   Pages 112-136

7. Back Matter

   Pages 137-149

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Structural exchange rate modeling has proven extremely difficult during the recent post-1973 float. The disappointment climaxed with the papers of Meese and Rogoff (1983a, 1983b), who showed that a "naive" random walk model distinctly dominated received theoretical models in terms of predictive performance for the major dollar spot rates. One purpose of this monograph is to seek the reasons for this failure by exploring the temporal behavior of seven major dollar exchange rates using nonstructural time-series methods. The Meese-Rogoff finding does not mean that exchange rates evolve as random walks; rather it simply means that the random walk is a better stochastic approximation than any of their other candidate models. In this monograph, we use optimal model specification techniques, including formal unit root tests which allow for trend, and find that all of the exchange rates studied do in fact evolve as random walks or random walks with drift (to a very close approximation). This result is consistent with efficient asset markets, and provides an explanation for the Meese-Rogoff results. Far more subtle forces are at work, however, which lead to interesting econometric problems and have implications for the measurement of exchange rate volatility and moment structure. It is shown that all exchange rates display substantial conditional heteroskedasticity. A particularly reasonable parameterization of this conditional heteroskedasticity, which captures the observed clustering of prediction error variances, is developed in Chapter 2.

• Finance
• distribution
• dynamics
• exchange rates
• modeling
• statistics
• time series
• value-at-risk
• volatility

• Division of Research and Statistics, Board of Governors of the Federal Reserve System, USA

  Francis X. Diebold

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