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Exploring Volatility clustering financial markets and its implication

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  • Enow, Samuel Tabot

    (Research associate, IIE Varsity College, Durban)

Abstract

Volatility clustering is a prominent feature of financial markets exhibiting persistent fluctuations in volatility over time. Its characteristics such as long memory, asymmetry and varying cluster durations pose challenges for market participants although it may also present some opportunities. The aim of this study was to investigate the historical patterns and statistical properties of volatility clustering across different financial markets. This study used a GARCH and ARCH model for four stock markets from June 14, 2018 to June 14, 2023. The findings revealed the presence of volatility clustering in line with prior study. These clustering which may be due to the recent episodes in financial markets such as the covid-19 poses significant risk for traders and active market participants. Hence, regulatory authorities need to implement measures to enhance market resilience, sufficient liquidity and regulate high-frequency trading activities to mitigate systemic risk.

Suggested Citation

  • Enow, Samuel Tabot, 2023. "Exploring Volatility clustering financial markets and its implication," Journal of Economic and Social Development, Clinical Journals Press, vol. 10(02), pages 01-05, September.
    • Handle: RePEc:ris:joeasd:0034
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    1. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    2. Farooq Malik & Bradley Ewing & James Payne, 2005. "Measuring volatility persistence in the presence of sudden changes in the variance of Canadian stock returns," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 1037-1056, August.
    3. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    4. Pereira, João Pedro & Zhang, Harold H., 2010. "Stock Returns and the Volatility of Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 1077-1110, August.
    5. Samuel Tabot Enow, 2022. "Overreaction And Underreaction During The Covid-19 Pandemic In The South African Stock Market And Its Implications," Eurasian Journal of Business and Management, Eurasian Publications, vol. 10(1), pages 19-26.
    6. Mert Topcu & Ibrahim Yagli & Furkan Emirmahmutoglu, 2021. "COVID-19 and stock market volatility: A time-varying perspective," Economics Bulletin, AccessEcon, vol. 41(3), pages 1681-1689.
    7. Kuntara Pukthuanthong-Le & Nuttawat Visaltanachoti, 2009. "Idiosyncratic volatility and stock returns: a cross country analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1269-1281.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Izani Ibrahim & Kamilah Kamaludin & Sheela Sundarasen, 2020. "COVID-19, Government Response, and Market Volatility: Evidence from the Asia-Pacific Developed and Developing Markets," Economies, MDPI, vol. 8(4), pages 1-22, November.
    10. Juan Carlos Ruilova & Pedro Alberto Morettin, 2020. "Parsimonious Heterogeneous ARCH Models for High Frequency Modeling," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    11. Bera, Anil K & Higgins, Matthew L, 1993. "ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-366, December.
    12. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    13. Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank.
    14. Samuel Tabot Enow, 2022. "Price Clustering in International Financial Markets during the COVID-19 Pandemic and Its Implications," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 10(2), pages 46-53.
    15. Nelson, Daniel B., 1990. "Stationarity and Persistence in the GARCH(1,1) Model," Econometric Theory, Cambridge University Press, vol. 6(3), pages 318-334, September.
    16. 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.
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    Cited by:

    1. Enow, Samuel Tabot, 2023. "Time-Varying Properties of Stock Returns: An empirical Perspective," Journal of Economic and Social Development, Clinical Journals Press, vol. 10(02), pages 01-05, September.

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    More about this item

    Keywords

    Volatility Clustering; GARCH Model; ARCH Model; Financial Markets;
    All these keywords.

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists

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