IDEAS home Printed from https://ideas.repec.org/a/eaa/ijaeqs/v2y2005i4_8.html
   My bibliography  Save this article

Modeling Market Volatility in Emerging Markets: The case of Daily Data in Amman Stock Exchange 1992-2004

Author

Listed:
  • ROUSAN, Raya
  • AL-KHOURI, Ritab

Abstract

This paper attempts to investigate the volatility of the Jordanian emerging stock market using daily observations from Amman Stock Exchange Composite Index (ASE) for the period from January 1, 1992 through December 31, 2004. Preliminary analysis of the data shows significant departure from normality. Moreover, returns and residuals show a significant level of serial correlation which is related to the conditional heteroskedasticity due to the time varying volatility. These results suggest that ARCH and GARCH models can provide good approximation for capturing the characteristics of ASE. The empirical analysis supports the hypothesis of symmetric volatility; hence, both good and bad news of the same magnitude have the same impact on the volatility level. Moreover, the volatility persists in the market for a long period of time, which makes ASE market inefficient; therefore, returns can be easily predicted and forecasted.

Suggested Citation

  • ROUSAN, Raya & AL-KHOURI, Ritab, 2005. "Modeling Market Volatility in Emerging Markets: The case of Daily Data in Amman Stock Exchange 1992-2004," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 99-118.
  • Handle: RePEc:eaa:ijaeqs:v:2:y2005:i:4_8
    as

    Download full text from publisher

    File URL: http://www.usc.es/economet/reviews/ijaeqs248.pdf
    Download Restriction: No
    ---><---

    References listed on IDEAS

    as
    1. Kate Phylaktis & Manolis Kavussanos & Gikas Manalis, 1999. "Price Limits and Stock Market Volatility in the Athens Stock Exchange," European Financial Management, European Financial Management Association, vol. 5(1), pages 69-84, March.
    2. Craig A. Depken, 2001. "Good News, Bad News and Garch Effects in Stock Return Data," Journal of Applied Economics, Taylor & Francis Journals, vol. 4(2), pages 313-327, November.
    3. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    4. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    5. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    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 & Ray Y. Chou & Narayanan Jayaraman & Kenneth F. Kroner - L, 1991. "es modéles ARCH en finance : un point sur la théorie et les résultats empiriques," Annals of Economics and Statistics, GENES, issue 24, pages 1-59.
    2. repec:adr:anecst:y:1991:i:24:p:01 is not listed on IDEAS
    3. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    4. 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.
    5. Patricia Fraser & David Power, 1997. "Stock return volatility and information: an empirical analysis of Pacific Rim, UK and US equity markets," Applied Financial Economics, Taylor & Francis Journals, vol. 7(3), pages 241-253.
    6. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    7. Chuang, Wen-I & Huang, Teng-Ching & Lin, Bing-Huei, 2013. "Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 168-187.
    8. 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.
    9. 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.
    10. Takaishi, Tetsuya, 2017. "Rational GARCH model: An empirical test for stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 451-460.
    11. Wen-Ling Lin & Takatoshi Ito, 1994. "Price Volatility and Volume Spillovers between the Tokyo and New York Stock Markets," NBER Chapters, in: The Internationalization of Equity Markets, pages 309-343, National Bureau of Economic Research, Inc.
    12. Sandmann, G. & Koopman, Siem, 1996. "Maximum likelihood estimation of stochastic volatility models," LSE Research Online Documents on Economics 119161, London School of Economics and Political Science, LSE Library.
    13. Gary McCormick & Dan W. French, 2016. "Effects of frequent information disclosure: the case of daily net asset value reporting for closed-end investment companies," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 107-122, January.
    14. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    15. Daniel Smith, 2008. "Testing for structural breaks in GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(10), pages 845-862.
    16. Michail Karoglou, 2009. "Stock Market Efficiency before and after a Financial Liberalisation Reform," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(3), pages 315-340, September.
    17. Pandey, Ajay, 2003. "Modeling and Forecasting Volatility in Indian Capital Markets," IIMA Working Papers WP2003-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    18. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, vol. 25(3), pages 238-254, September.
    19. Choudhry, Taufiq, 1996. "Stock market volatility and the crash of 1987: evidence from six emerging markets," Journal of International Money and Finance, Elsevier, vol. 15(6), pages 969-981, December.
    20. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Sensitivity of Value at Risk estimation to NonNormality of returns and Market capitalization," MPRA Paper 56307, University Library of Munich, Germany, revised 26 May 2014.
    21. Wagner, Niklas, 2004. "Time-varying moments, idiosyncratic risk, and an application to hot-issue IPO aftermarket returns," Research in International Business and Finance, Elsevier, vol. 18(1), pages 59-72, April.

    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:eaa:ijaeqs:v:2:y2005:i:4_8. 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: M. Carmen Guisan (email available below). General contact details of provider: http://www.usc.es/economet/eaa.htm .

    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.