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Modelling the volatility in East European emerging stock markets: evidence on Hungary and Poland


  • Sunil Poshakwale
  • Victor Murinde


In this paper, stock market volatility in the East European emerging markets of Hungary and Poland is investigated using daily indexes. The results suggest the presence of non-linearity in the indexes through the BDSL statistic, while the presence of conditional heteroscedasticity is detected through LM tests. Conditional volatility is then modelled as a GARCH process; however, as measured by a GARCH-M model, this does not seems to be priced in the Hungarian and Polish stock markets. Moreover, the evidence rejects the Martingale hypothesis that future changes of stock prices in the two markets are orthogonal to past information. The well-known day-of-the-week effect, reflected in significantly positive Friday and negative Monday returns, does not seem to be present in these markets. While a marked decline in conditional volatility in the Polish market after June 1995 may be explained by appreciating Zloty exchange rates against the German Mark and increasing integration with developed markets, a similar (but less consistent) pattern between exchange rates (Hungarian against German and UK currencies) and conditional volatility is found for the Hungarian market.

Suggested Citation

  • Sunil Poshakwale & Victor Murinde, 2001. "Modelling the volatility in East European emerging stock markets: evidence on Hungary and Poland," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 445-456.
  • Handle: RePEc:taf:apfiec:v:11:y:2001:i:4:p:445-456
    DOI: 10.1080/096031001300314009

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    References listed on IDEAS

    1. Francis X. Diebold, 1986. "Temporal aggregation of ARCH processes and the distribution of asset returns," Special Studies Papers 200, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Högholm, Kenneth & Knif, Johan, 2009. "The impact of portfolio aggregation on day-of-the-week effect: Evidence from Finland," Global Finance Journal, Elsevier, vol. 20(1), pages 67-79.
    2. repec:taf:oabmxx:v:3:y:2016:i:1:p:1147111 is not listed on IDEAS
    3. Gebka, Bartosz & Serwa, Dobromil, 2007. "Intra- and inter-regional spillovers between emerging capital markets around the world," Research in International Business and Finance, Elsevier, vol. 21(2), pages 203-221, June.
    4. Piotr Fiszeder & Witold Orzeszko, 2012. "Nonparametric Verification of GARCH-Class Models for Selected Polish Exchange Rates and Stock Indices," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 430-449, November.
    5. Kovačić, Zlatko, 2007. "Forecasting volatility: Evidence from the Macedonian stock exchange," MPRA Paper 5319, University Library of Munich, Germany.
    6. Strawinski, Pawel & Slepaczuk, Robert, 2008. "Analysis of HF data on the WSE in the context of EMH," MPRA Paper 9532, University Library of Munich, Germany.
    7. Abdelkader Derbali & Slaheddine Hallara & David McMillan, 2016. "Day-of-the-week effect on the Tunisian stock market return and volatility," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1147111-114, December.
    8. Ana Filipa Carvalho & Jose Sa da Costa & Jose Assis Lopes, 2006. "A systematic modelling strategy for futures markets volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 819-833.
    9. Wang, Ping & Moore, Tomoe, 2009. "Sudden changes in volatility: The case of five central European stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 33-46, February.
    10. Pawel STRAWINSKI & Robert SLEPACZUK, 2008. "Analysis Of High Frequency Data On The Warsaw Stock Exchange In The Context Of Efficient Market Hypothesis," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 306-319.
    11. Prashant Joshi, 2010. "Modeling Volatility in Emerging Stock Markets Of India And China," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 86-94, January.
    12. repec:rjr:romjef:v::y:2017:i:3:p:37-53 is not listed on IDEAS
    13. de, Vries Frans & Montagnoli, Alberto, 2009. "Carbon trading thickness and market efficiency: A non-parametric test," Stirling Economics Discussion Papers 2009-22, University of Stirling, Division of Economics.
    14. Taufeeque Ahmad Siddiqui & Isha Narula, 2013. "Market Efficiency and Anomalies: Evidences from S&P CNX NIFTY," Vision, , vol. 17(3), pages 233-245, September.

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