IDEAS home Printed from https://ideas.repec.org/a/ddj/fseeai/y2024i2p41-52.html
   My bibliography  Save this article

Exploring Advanced GARCH Models for Analyzing Asymmetric Volatility Dynamics for the Emerging Stock Market in Hungary: An Empirical Case Study

Author

Listed:
  • Shreevastava Aman

    (PG Department of Commerce&Management, Purnea University, Purnea, India)

  • Raza Shahil

    (PG Department of Commerce&Management, Purnea University, Purnea, India)

  • Bharat Kumar Meher

    (PG Department of Commerce&Management, Purnea University, Purnea, India)

  • Ramona Birau

    (University of Craiova, “Eugeniu Carada” Doctoral School of Economic Sciences, Craiova, Romania)

  • Anand Abhishek

    (PG Department of Economics, Purnea University, Purnea, India)

  • Mircea Laurentiu Simion

    (University of Craiova, “Eugeniu Carada” Doctoral School of Economic Sciences, Craiova, Romania)

  • Nadia Tudora Cirjan

    (National Agency for Fiscal Administration (ANAF), Regional Directorate General of Public Finance Craiova)

Abstract

The study was conducted on BUX Index volatility for the post-2008 (from 2011) global financial crisis period using advanced GARCH models (GARCH, TGARCH, EGARCH, IGARCH, PARCH, APARCH). Based on parameters and test results appropriate model was chosen (APARCH (1,1) at Student’s t distribution) to study volatility, the presence of asymmetry, leverage effect, volatility clustering, and decay factor. Test results were linked with the macro and microenvironment (Political instability, Geopolitical crisis, Unemployment, Inflation, COVID-19, Slowdown, etc.) of the index and unique features of the index have been discovered (Like a sudden huge dip between 2020-2022). The study through mathematical and econometrics terms establishes causal links among the variables affecting the index. The paper is relevant to both investors and policymakers as BUX is one of the most important indicators as far as stock market in Hungary is concerned.

Suggested Citation

  • 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.
    • Handle: RePEc:ddj:fseeai:y:2024:i:2:p:41-52
    DOI: https://doi.org/10.35219/eai15840409409
    as

    Download full text from publisher

    File URL: http://eia.feaa.ugal.ro/images/eia/2024_2/Aman_et_al.pdf
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.35219/eai15840409409?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Bollerslev, Tim & Russell, Jeffrey & Watson, Mark (ed.), 2010. "Volatility and Time Series Econometrics: Essays in Honor of Robert Engle," OUP Catalogue, Oxford University Press, number 9780199549498.
    3. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Latasha Mohapatra & Adel M. Sarea, 2020. "The Impact of COVID-19 on Price Volatility of Crude Oil and Natural Gas Listed on Multi Commodity Exchange of India," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 422-431.
    4. Scheicher, Martin, 2001. "The Comovements of Stock Markets in Hungary, Poland and the Czech Republic," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 27-39, January.
    5. 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.
    6. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    7. Maria Kasch-Haroutounian & Simon Price, 2001. "Volatility in the transition markets of Central Europe," Applied Financial Economics, Taylor & Francis Journals, vol. 11(1), pages 93-105.
    8. Ma, Dandan & Zhang, Yunhan & Ji, Qiang & Zhao, Wan-Li & Zhai, Pengxiang, 2024. "Heterogeneous impacts of climate change news on China's financial markets," International Review of Financial Analysis, Elsevier, vol. 91(C).
    9. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    10. Madhusudan Karmakar & Udayan Sharma, 2020. "Measuring quantile risk hedging effectiveness: a GO-GARCH-EVT-copula approach," Applied Economics, Taylor & Francis Journals, vol. 52(48), pages 5244-5262, October.
    11. Miloslav Vošvrda & Filip Žikeš, 2004. "An Application of the Garch-t Model on Central European Stock Returns," Prague Economic Papers, Prague University of Economics and Business, vol. 2004(1), pages 26-39.
    12. Katarzyna Czech & Michał Wielechowski & Pavel Kotyza & Irena Benešová & Adriana Laputková, 2020. "Shaking Stability: COVID-19 Impact on the Visegrad Group Countries’ Financial Markets," Sustainability, MDPI, vol. 12(15), pages 1-19, August.
    13. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    14. Bharat Kumar Meher & Puja Kumari & Ramona Birau & Cristi Spulbar & Abhishek Anand & Ion Florescu, 2024. "Forecasting Volatility Spillovers Using Advanced GARCH Models: Empirical Evidence for Developed Stock Markets from Austria and USA," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 16-29.
    15. Canepa, Alessandra, 2024. "Inflation dynamics and persistence: The importance of the uncertainty channel," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    Full references (including those not matched with items on IDEAS)

    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. Krzysztof DRACHAL, 2017. "Volatility Clustering, Leverage Effects and Risk-Return Tradeoff in the Selected Stock Markets in the CEE Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-53, September.
    2. Kovačić, Zlatko, 2007. "Forecasting volatility: Evidence from the Macedonian stock exchange," MPRA Paper 5319, University Library of Munich, Germany.
    3. 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.
    4. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
    5. 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).
    6. repec:zbw:bofitp:2014_006 is not listed on IDEAS
    7. Erginbay UGURLU, 2014. "Forecasting Volatility: Evidence from the Bucharest Stock Exchange," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 1(1), pages 302-310, December.
    8. 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.
    9. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.
    10. Sabbaghi, Omid & Sabbaghi, Navid, 2011. "Carbon Financial Instruments, thin trading, and volatility: Evidence from the Chicago Climate Exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 399-407.
    11. 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.
    12. Javed Farrukh & Podgórski Krzysztof, 2017. "Tail Behavior and Dependence Structure in the APARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-48, July.
    13. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    14. Michał Adam & Piotr Bańbuła & Michał Markun, 2013. "Dependence and contagion between asset prices in Poland and abroad. A copula approach," NBP Working Papers 169, Narodowy Bank Polski.
    15. Laura Wallenius & Elena Fedorova & Sheraz Ahmed & Mikael Collan, 2017. "Surprise Effect of Euro Area Macroeconomic Announcements on CIVETS Stock Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(1), pages 55-71.
    16. Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
    17. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    18. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
    19. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    20. Kumar SANTOSH & Meher Kumar BHARAT & Ramona BIRAU & Mircea Laurentiu SIMION & Anand ABHISHEK & Singh MANOHAR, 2023. "Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-68.
    21. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

    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:ddj:fseeai:y:2024:i:2:p:41-52. 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: Gianina Mihai (email available below). General contact details of provider: https://edirc.repec.org/data/fegalro.html .

    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.