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Modelling Stock Returns in the G-7 and in Selected CEE Economies: A Non-linear GARCH Approach

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  • Bal??zs ??gert
  • Yosra Koubaa

Abstract

This paper investigates conditional variance patterns in daily return series of stock market indices in the G-7 and 6 selected economies of Central and Eastern Europe. For this purpose, various linear and asymmetric GARCH models are employed. The analysis is conducted for Canada, France, Germany, Italy, Japan, the UK and the US for which the TSX, CAC-40, DAX-100, BCI, Nikkei-225, FTSE-100 and DJ-30 indices are respectively considered over the period 1987 to 2002. Furthermore, the official indices of Czech, Hungarian, Polish, Russian, Slovak and Slovene stock markets are also studied, i.e. the PX-50, BUX, WIGI, RFS, SAX-16 and SBI, respectively, over 1991/1995 to 2002. The estimation results reveal that the selected stock returns for the G-7 can be reasonably well modelled using linear specifications whereas the overwhelming majority of the stock indices from Central and Eastern Europe can be much better characterised using asymmetric models. In other words, stock markets of the transition economies exhibit much more asymmetry because negative shocks hit much harder these markets than positive news. It also turns out that these changes do not occur in a smooth manner but happen pretty brusquely. This corroborates the usual observation that emerging stock markets may collapse much more suddenly and recover more slowly than G-7 stock markets.

Suggested Citation

  • Bal??zs ??gert & Yosra Koubaa, 2004. "Modelling Stock Returns in the G-7 and in Selected CEE Economies: A Non-linear GARCH Approach," William Davidson Institute Working Papers Series 2004-663, William Davidson Institute at the University of Michigan.
  • Handle: RePEc:wdi:papers:2004-663
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    References listed on IDEAS

    as
    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Hagerud, Gustaf E., 1997. "Specification Tests for Asymmetric GARCH," SSE/EFI Working Paper Series in Economics and Finance 163, Stockholm School of Economics.
    3. Fornari, Fabio & Mele, Antonio, 1996. "Modeling the changing asymmetry of conditional variances," Economics Letters, Elsevier, vol. 50(2), pages 197-203, February.
    4. Fornari, Fabio & Mele, Antonio, 1997. "Sign- and Volatility-Switching ARCH Models: Theory and Applications to International Stock Markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 49-65, Jan.-Feb..
    5. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Hartwell, Christopher A., 2014. "The impact of institutional volatility on financial volatility in transition economies : a GARCH family approach," BOFIT Discussion Papers 6/2014, Bank of Finland, Institute for Economies in Transition.
    2. Shreevastava Aman & Raza Shahil & Bharat Kumar Meher & Ramona Birau & Anand Abhishek & Mircea Laurentiu Simion & Nadia Tudora Cirjan, 2024. "Exploring Advanced GARCH Models for Analyzing Asymmetric Volatility Dynamics for the Emerging Stock Market in Hungary: An Empirical Case Study," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 41-52.
    3. Ian Babetskii & Luboš Komárek & Zlatuše Komárková, 2007. "Financial Integration of Stock Markets among New EU Member States and the Euro Area," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(7-8), pages 341-362, September.
    4. Borusyak, K., 2011. "Nonlinear Dynamics of the Russian Stock Market in Problems of Risk Management," Journal of the New Economic Association, New Economic Association, issue 11, pages 85-105.
    5. repec:zbw:bofitp:2014_006 is not listed on IDEAS
    6. Hartwell, Christopher A., 2014. "The impact of institutional volatility on financial volatility in transition economies: a GARCH family approach," BOFIT Discussion Papers 6/2014, Bank of Finland Institute for Emerging Economies (BOFIT).
    7. Anita Radman Peša & Mejra Festić, 2012. "Testing the "EU Announcement Effect" on Stock Market Indices and Macroeconomic Variables in Croatia Between 2000 and 2010," Prague Economic Papers, Prague University of Economics and Business, vol. 2012(4), pages 450-469.
    8. repec:prg:jnlpep:v:2013:y:2013:i:4:id:434:p:450-469 is not listed on IDEAS

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    More about this item

    Keywords

    volatility modelling; conditional variance; non-linearity; asymmetric GARCH; G-7; transition economies;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • P52 - Political Economy and Comparative Economic Systems - - Comparative Economic Systems - - - Comparative Studies of Particular Economies

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