IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/94201.html
   My bibliography  Save this paper

Stock Market Volatility Analysis using GARCH Family Models: Evidence from Zimbabwe Stock Exchange

Author

Listed:
  • Bonga, Wellington Garikai

Abstract

Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using monthly return series consisting of 109 observations from January 2010 to January 2019. ARCH effects test confirmed the use of GARCH family models. Symmetric and asymmetric models were used namely: GARCH(1,1), GARCH-M(1,1), IGARCH(1,1) and EGARCH(1,1). Post-estimation test for further ARCH effects were done for each model to confirm its efficiency for policy. EGARCH(1,1) turned to be the best model using both the AIC and SIC criterions; with the presence of asymmetry found to be significant. The study concludes that positive and negative shocks have different effects on the stock market returns series. Bad and good news will increase volatility of stock market returns in different magnitude. This simply imply that investors on the Zimbabwean stock exchange react differently to information depending be it positive or negative in making investment decisions.

Suggested Citation

  • Bonga, Wellington Garikai, 2019. "Stock Market Volatility Analysis using GARCH Family Models: Evidence from Zimbabwe Stock Exchange," MPRA Paper 94201, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:94201
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/94201/1/MPRA_paper_94201.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karunanithy Banumathy & Ramachandran Azhagaiah, 2015. "Modelling Stock Market Volatility: Evidence from India," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 13(1 (Spring), pages 27-41.
    2. Hammoudeh, Shawkat & Li, Huimin, 2008. "Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 47-63.
    3. Priviledge Cheteni, 2017. "Stock Market Volatility Using GARCH Models: Evidence from South Africa and China Stock Markets," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 237-245.
    4. 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.
    5. Olatundun Janet Adelegan, 2009. "The Derivatives Market in South Africa: Lessons for Sub-Saharan African Countries," IMF Working Papers 2009/196, International Monetary Fund.
    6. Paul H. Kupiec, 1991. "Stock market volatility in OECD countries: recent trends, consequences for the real economy, and proposals for reform," Finance and Economics Discussion Series 165, Board of Governors of the Federal Reserve System (U.S.).
    7. Iorember, Paul & Sokpo, Joseph & Usar, Terzungwe, 2017. "Inflation and Stock Market Returns Volatility: Evidence from the Nigerian Stock Exchange 1995Q1-2016Q4: An E-GARCH Approach," MPRA Paper 85656, University Library of Munich, Germany.
    8. Umar Bida Ndako, 2012. "Financial liberalization, structural breaks and stock market volatility: evidence from South Africa," Applied Financial Economics, Taylor & Francis Journals, vol. 22(15), pages 1259-1273, August.
    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. Tran, Thuy Nhung, 2022. "The Volatility of the Stock Market and Financial Cycle: GARCH Family Models," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(1), pages 151-168.
    2. 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.

    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. Neifar, Malika, 2020. "Stock Market Volatility Analysis: A Case Study of TUNindex," MPRA Paper 99140, University Library of Munich, Germany.
    2. Elie Bouri & Georges Azzi, 2014. "On the Dynamic Transmission of Mean and Volatility across the Arab Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 13(3), pages 279-304, December.
    3. Altaf Muhammad & Zhang Shuguang, 2015. "Impact Of Structural Shifts on Variance Persistence in Asymmetric Garch Models: Evidence From Emerging Asian and European Markets," Romanian Statistical Review, Romanian Statistical Review, vol. 63(1), pages 57-70, March.
    4. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    5. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    6. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    7. Guillermo Benavides & Isela Elizabeth Téllez-León & Francisco Venegas-Martínez, 2015. "Effects of Volatility of the Exchange Rate on Inflation Expectations and Growth Prospects in Mexico (2002-2014)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 63-78, November.
    8. Kumar Arya & Sahoo Jyotirmayee & Sahoo Jyotsnarani & Nanda Subhashree & Debyani Devi, 2024. "Exploring Asymmetric GARCH Models for Predicting Indian Base Metal Price Volatility," Folia Oeconomica Stetinensia, Sciendo, vol. 24(1), pages 105-123.
    9. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2021. "How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    10. Nsofor Ebele Sabina & Takon Samuel Manyo & Ugwuegbe Sebastine Ugochukwu, 2017. "Modeling Exchange Rate Volatility and Economic Growth in Nigeria," Noble International Journal of Economics and Financial Research, Noble Academic Publsiher, vol. 2(6), pages 88-97, June.
    11. Naseem Al Rahahleh & Robert Kao, 2018. "Forecasting Volatility: Evidence from the Saudi Stock Market," JRFM, MDPI, vol. 11(4), pages 1-18, November.
    12. Kollias, Christos & Manou, Efthalia & Papadamou, Stephanos & Stagiannis, Apostolos, 2011. "Stock markets and terrorist attacks: Comparative evidence from a large and a small capitalization market," European Journal of Political Economy, Elsevier, vol. 27(S1), pages 64-77.
    13. Anas Eisa Abdelkreem Mohammed & Henry Mwambi & Bernard Omolo, 2024. "Time-Varying Correlations between JSE.JO Stock Market and Its Partners Using Symmetric and Asymmetric Dynamic Conditional Correlation Models," Stats, MDPI, vol. 7(3), pages 1-16, July.
    14. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    15. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    16. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    17. Dimitrios Kartsonakis-Mademlis & Nikolaos Dritsakis, 2022. "Asymmetric volatility transmission in Japanese stock market in the presence of structural breaks," The Japanese Economic Review, Springer, vol. 73(4), pages 647-677, October.
    18. Neifar, Malika, 2020. "Multivariate GARCH Approaches: case of major sectorial Tunisian stock markets," MPRA Paper 99658, University Library of Munich, Germany.
    19. Kamaldeen Ibraheem Nageri, 2019. "Evaluating Voltality Persistence Of Stock Returtn In The Pre And Post 2008-2009 Financial Meltdown," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 8(3), pages 75-94.
    20. repec:ipg:wpaper:2014-401 is not listed on IDEAS
    21. Yeonjeong Lee & Seong-Min Yoon, 2020. "Dynamic Spillover and Hedging among Carbon, Biofuel and Oil," Energies, MDPI, vol. 13(17), pages 1-19, August.

    More about this item

    Keywords

    Stock Market; Volatility; ARCH; GARCH; IGARCH; GARCH-M; EGARCH; Risk Premium; Zimbabwe;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • N27 - Economic History - - Financial Markets and Institutions - - - Africa; Oceania
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:94201. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.