IDEAS home Printed from https://ideas.repec.org/a/ukm/jlekon/v55y2021i2p15-28.html
   My bibliography  Save this article

Performance Analysis of GARCH Family Models in Three Time-frames

Author

Listed:
  • Hossain, Md. Jamal

    (School of Mathematical Sciences Universiti Sains Malaysia 11800 USM Penang MALAYSIA. Department of Applied Mathematics Noakhali Science and Technology University Noakhali-3814 BANGLADESH)

  • Akter, Sadia

    (Department of Accounting and Information Systems University of Rajshahi Rajshahi-6205 BANGLADESH.)

  • Ismail, Mohd Tahir

    (School of Mathematical Sciences Universiti Sains Malaysia 11800 USM Penang MALAYSIA.)

Abstract

The proposed alternative p-value method can be used in finding the best performing models. The rank of the p-values namely t-test and z-test statistics can overcome the constraint imposed when using the Mean Absolute Percentage Error as the measurement error. It is crucial to select the right model in the right period so that the model can interpret volatility correctly. This study aimed to provide empirical analyses on the volatility of the Dhaka Stock Exchange market during the market crash in 2011. Three sub-samples were considered to represent pre-crisis, crisis, and post-crisis between November 16, 2009 to July 31, 2013 representing 889 observations. Various GARCH family models were fitted in order to capture the volatility and their performances were compared

Suggested Citation

  • Hossain, Md. Jamal & Akter, Sadia & Ismail, Mohd Tahir, 2021. "Performance Analysis of GARCH Family Models in Three Time-frames," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(2), pages 15-28.
    • Handle: RePEc:ukm:jlekon:v:55:y:2021:i:2:p:15-28
    DOI: http://dx.doi.org/10.17576/JEM-2021-5502-2
    as

    Download full text from publisher

    File URL: http://www.ukm.my/jem/wp-content/uploads/2021/10/jeko_552-2.pdf
    Download Restriction: no
    File URL: https://libkey.io/http://dx.doi.org/10.17576/JEM-2021-5502-2?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. 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.
    2. Neveen Ahmed, 2018. "The effect of the financial crisis on the dynamic relation between foreign exchange and stock returns," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 45(5), pages 994-1031, October.
    3. Samer AM Al‐Rjoub & Hussam Azzam, 2012. "Financial crises, stock returns and volatility in an emerging stock market: the case of Jordan," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 39(2), pages 178-211, May.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Anwar Hasan Abdullah Othman & Syed Musa Alhabshi & Razali Haron, 2019. "The effect of symmetric and asymmetric information on volatility structure of crypto-currency markets," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 11(3), pages 432-450, May.
    6. Cowell, Frank A & Jenkins, Stephen P, 1995. "How Much Inequality Can We Explain? A Methodology and an Application to the United States," Economic Journal, Royal Economic Society, vol. 105(429), pages 421-430, March.
    7. Islam , K. M. Zahidul & Ahmed, Sayed Farrukh, 2015. "Stock Market Crash and Stock Return Volatility: Empirical Evidence from Dhaka Stock Exchange," Bangladesh Development Studies, Bangladesh Institute of Development Studies (BIDS), vol. 38(3), pages 25-34, September.
    8. Tetsuji Tanaka & Jin Guo, 2020. "How does the self-sufficiency rate affect international price volatility transmissions in the wheat sector? Evidence from wheat-exporting countries," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    9. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
    10. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    11. McIver, Ron P. & Kang, Sang Hoon, 2020. "Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 54(C).
    12. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    13. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    14. Broto, Carmen & Lamas, Matías, 2020. "Is market liquidity less resilient after the financial crisis? Evidence for US Treasuries," Economic Modelling, Elsevier, vol. 93(C), pages 217-229.
    15. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    16. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-158, February.
    17. Robert Engle, 2018. "Systemic Risk 10 Years Later," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 125-152, November.
    18. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    19. Bathia, Deven & Bouras, Christos & Demirer, Riza & Gupta, Rangan, 2020. "Cross-border capital flows and return dynamics in emerging stock markets: Relative roles of equity and debt flows," Journal of International Money and Finance, Elsevier, vol. 109(C).
    20. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-235, April.
    21. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    22. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    23. Engle, Robert F, 1990. "Stock Volatility and the Crash of '87: Discussion," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 103-106.
    24. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    25. 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.
    26. Louis H. Ederington & Wei Guan, 2005. "Forecasting volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(5), pages 465-490, May.
    27. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    28. 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)

    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. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    3. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
    4. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    5. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    6. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    7. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038, Elsevier.
    8. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    9. 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.
    10. Hentschel, Ludger, 1995. "All in the family Nesting symmetric and asymmetric GARCH models," Journal of Financial Economics, Elsevier, vol. 39(1), pages 71-104, September.
    11. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Radovan Parrák, 2013. "The Economic Valuation of Variance Forecasts: An Artificial Option Market Approach," Working Papers IES 2013/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2013.
    13. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    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., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • 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).
    15. Saker Sabkha & Christian de Peretti, 2018. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Working Papers hal-01710398, HAL.
    16. 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.
    17. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    18. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    19. Marcin Fałdziński & Piotr Fiszeder & Witold Orzeszko, 2020. "Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression," Energies, MDPI, vol. 14(1), pages 1-18, December.
    20. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.

    More about this item

    Keywords

    GARCH models; crisis; error statistics; p-value; volatility;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:ukm:jlekon:v:55:y:2021:i:2:p:15-28. 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: Muhammad Asri Abd Ghani (email available below). General contact details of provider: https://edirc.repec.org/data/feukmmy.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.