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

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  • Helmut Herwartz
  • Hans‐Eggert Reimers

Abstract

We analyse 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). To account for volatility clustering we fit a GARCH(1,1)‐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. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Helmut Herwartz & Hans‐Eggert Reimers, 2002. "Empirical modelling of the DEM/USD and DEM/JPY foreign exchange rate: Structural shifts in GARCH‐models and their implications," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 18(1), pages 3-22, January.
    • Handle: RePEc:wly:apsmbi:v:18:y:2002:i:1:p:3-22
    DOI: 10.1002/asmb.451
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    Cited by:

    1. Makram El-Shagi & Sebastian Giesen, 2013. "Testing for Structural Breaks at Unknown Time: A Steeplechase," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 101-123, January.
    2. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Other publications TiSEM a797e4a8-12cf-4ac5-9fae-b, Tilburg University, School of Economics and Management.
    3. Gozgor, Giray & Nokay, Pinar, 2011. "Comparing forecast performances among volatility estimation methods in the pricing of european type currency options of USD-TL and Euro-TL," MPRA Paper 34369, University Library of Munich, Germany.
    4. Rachna Mahalwala, 2022. "Analysing exchange rate volatility in India using GARCH family models," SN Business & Economics, Springer, vol. 2(9), pages 1-16, September.
    5. Cizek, P., 2010. "Modelling Conditional Heteroscedasticity in Nonstationary Series," Discussion Paper 2010-84, Tilburg University, Center for Economic Research.

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    More about this item

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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