Empirical modelling of the DEM/USD and DEM/JPY foreign exchange rate: Structural shifts in GARCH‐models and their implications

We analyze daily changes of two log foreign exchange (FX) rates involving the Deutsche Mark (DEM) for the period 1975 - 1998, namely FX-rates measured against the US dollar (USD) and the Japanese yen (JPY). Ta account for volatility e1ustering we fit a GARCH(l,l)-model with leptokurtic innovations. Its parameters are not stable over the sample period and two separate variance regimes are selected for both exchange rate series. The identified points of structural change are close to a change of the monetary policies in the US and Japan, the latter of which is followed by a long period of decreasing asset prices. Having identified subperiods of homogeneous volatility dynamics we concentrate on stylized facts to distinguish these volatility regimes. The bottom level of estimated volatility turns out be considerably higher during the second part of the sample period for both exchange rates. A similar result holds for the average level of volatility and for implied volatility of heavily traded at the money options.

[1]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[2]  Tim Bollerslev,et al.  Chapter 49 Arch models , 1994 .

[3]  W. R. Buckland,et al.  Distributions in Statistics: Continuous Multivariate Distributions , 1974 .

[4]  J. Duan THE GARCH OPTION PRICING MODEL , 1995 .

[5]  G. Box,et al.  On a measure of lack of fit in time series models , 1978 .

[6]  Stephen L Taylor,et al.  Modelling Financial Time Series , 1987 .

[7]  S. Heston,et al.  A Closed-Form GARCH Option Valuation Model , 2000 .

[8]  T. Bollerslev,et al.  A CONDITIONALLY HETEROSKEDASTIC TIME SERIES MODEL FOR SPECULATIVE PRICES AND RATES OF RETURN , 1987 .

[9]  Francis X. Dieobold Modeling The persistence Of Conditional Variances: A Comment , 1986 .

[10]  Christopher G. Lamoureux,et al.  Persistence in Variance, Structural Change, and the GARCH Model , 1990 .

[11]  R. Lumsdaine,et al.  Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models , 1996 .

[12]  F. Black,et al.  The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.

[13]  Chia-Shang James Chu,et al.  Detecting parameter shift in garch models , 1995 .

[14]  Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets , 1999 .

[15]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[16]  W. D. Lastrapes,et al.  Exchange Rate Volatility and U.S. Monetary Policy: An ARCH Application , 1989 .

[17]  Bruce E. Hansen,et al.  Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator , 1994, Econometric Theory.

[18]  James D. Hamilton,et al.  Autoregressive conditional heteroskedasticity and changes in regime , 1994 .

[19]  Anil K. Bera,et al.  A test for normality of observations and regression residuals , 1987 .

[20]  J. Wooldridge,et al.  Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances , 1992 .

[21]  H. White A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .

[22]  Takatoshi Ito,et al.  Explaining Asset Bubbles in Japan , 1995 .

[23]  Daniel B. Nelson Stationarity and Persistence in the GARCH(1,1) Model , 1990, Econometric Theory.

[24]  R. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[25]  Christian M. Hafner,et al.  Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis , 2001 .

[26]  Lawrence Harris,et al.  S&P 500 Cash Stock Price Volatilities , 1989 .