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Stock price fluctuations and GARCH modelling of stock market indexes

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  • Bistra Radeva

    (University of Economics, Varna, Bulgaria)

Abstract

The purpose of this paper is to show whether volatility clustering, as measured by the General autoregressive conditional heteroscedasticity - GARCH (1,1), can be explained by the information flow. The paper examines the stock indexes through several commonly used models: Zivot- Andrews unit root test, employed to test for the presence of structural breaks; the relationship between price and volume movements; passive investment strategy (profitability and risk of long-term investment); application of the GARCH model. The data source of the survey is provided by kaggle, containing information about stock indices for the period 01.01.1970 – 16.11.2018. All calculations are made using the statistical software R, version 3.3.4. (R Core Team, 2017). The results of the analysis point to the systematicity of the volatility study.

Suggested Citation

  • Bistra Radeva, 2019. "Stock price fluctuations and GARCH modelling of stock market indexes," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 3, pages 6-19.
    • Handle: RePEc:kab:journl:y:2019:i:3:p:6-19
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    File URL: http://eknigibg.net/Volume5/Issue3/spisanie-br3-2019_pp.6-19.pdf
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    References listed on IDEAS

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    1. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Brumm, Johannes & Grill, Michael & Kubler, Felix & Schmedders, Karl, 2015. "Margin regulation and volatility," Journal of Monetary Economics, Elsevier, vol. 75(C), pages 54-68.
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