Abstract

One of the important factors that can affect the decision of investors to move to an emerging economy is the degree of economic and financial stability of that country. Financial communities are keen to know the extent to which movements in the macroeconomic variables of a country can be reliably predicted. The efficiency of forecasts and the effectiveness of policies depend on the correct specification of the models that are used in explaining the behaviour of variables. Given the large number of parameters and factors that can affect the behaviour of macroeconomic and financial variables over time, it is crucially important to use appropriate dynamic models that can better explain the performance of variables. The studies included in this volume have all tried to determine the most suitable model to explain the behaviour of financial markets in various emerging economies.

Keywords

Turkey Argentina Volatility Nigeria Venezuela 

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References

  1. Brunetti, C. and Christopher, L. (2000), Bivariate FIGARCH and fractional cointegration, Journal of Empirical Finance 7, 509–30.CrossRefGoogle Scholar
  2. Nowman, K. B. (1997), Gaussian estimation of single-factor continuous time models of the term structure of interest rates, Journal of Finance 52,1695–706.CrossRefGoogle Scholar
  3. Nowman, K. B. (2001), Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacific Financial Markets 8, 23–34.CrossRefGoogle Scholar
  4. Teyssière, G. (1998), Multivariate long-memory ARCH modeling for high frequency foreign exchange rates, GREQAM 98.Google Scholar

Copyright information

© Contributors 2005

Authors and Affiliations

  • Sima Motamen-Samadian

There are no affiliations available

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