IDEAS home Printed from https://ideas.repec.org/a/ris/joeasd/0034.html
   My bibliography  Save this article

Exploring Volatility clustering financial markets and its implication

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.jesd-online.com/articles/exploring-volatility-clustering-financial-markets-and-its-implication.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Juan Carlos Ruilova & Pedro Alberto Morettin, 2020. "Parsimonious Heterogeneous ARCH Models for High Frequency Modeling," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    3. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    4. McMillan, David G. & Speight, Alan E. H., 2001. "Non-ferrous metals price volatility: a component analysis," Resources Policy, Elsevier, vol. 27(3), pages 199-207, September.
    5. 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.
    6. David McMillan & Alan Speight, 2006. "Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(13), pages 959-972.
    7. Dennis Kristensen, 2009. "On stationarity and ergodicity of the bilinear model with applications to GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 125-144, January.
    8. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.
    9. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    10. Lumengo Bonga-Bonga & Tebogo Maake, 2021. "The Relationship between Carry Trade and Asset Markets in South Africa," JRFM, MDPI, vol. 14(7), pages 1-13, July.
    11. Andreu Sansó & Vicent Aragó & Josep Lluís Carrion, 2003. "Testing for Changes in the Unconditional Variance of Financial Time Series," DEA Working Papers 5, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    12. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, November.
    13. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    14. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    16. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    17. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    18. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    19. Phillip A. Cartwright & Natalija Riabko, 2016. "Further evidence on the explanatory power of spot food and energy commodities market prices for futures prices," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 579-605, October.
    20. David McMillan & Alan Speight, 2002. "Temporal aggregation, volatility components and volume in high frequency UK bond futures," The European Journal of Finance, Taylor & Francis Journals, vol. 8(1), pages 70-92.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:joeasd:0034. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marijan Cingula (email available below). General contact details of provider: http://www.eclinicalsci.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.