Titlebook: Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility; Christian M. Hafner Book 1998 Springer-Verlag Berlin

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linear

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ARCH Models and Extensions,plications. It became obvious that a powerful model class was developed that copes with the most important feature of financial time series, namely conditional heteroskedasticity. Especially after the fall of Bretton Woods and the subsequent free-floating period of exchange rates in the seventies, s

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Nonparametric and Semiparametric Models,The GARCH model fit outperformed the IGARCH and EGARCH model fits. Based on this analysis one might conclude that the conditional variance of FX returns is neither integrated (permanent memory), nor asymmetric. To show that this conclusion would be rash is the objective of this chapter.

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Conclusions and Outlook,ncy blocks, i.e. Dollar, Euro and Yen, is very likely to remain on a high level due to the discrepancies of the macroeconomic policies in these regions. Therefore, a correct understanding of the dynamic properties of volatility is crucial for reliable prediction of financial time series, which serves as the basis for policymaking.