IDEAS home Printed from https://ideas.repec.org/a/taf/jbemgt/v10y2009i4p349-360.html
   My bibliography  Save this article

Lithuanian stock market analysis using a set of Garch models

Author

Listed:
  • Deimante Teresiene

Abstract

This article analyses the main factors that influence stock price volatility. The author offers a three‐stage system for explaning a set of stock price volatility factors. The main point is to pay attention to investor's psychology as the main factor of price volatility. For practical analysis the returns of the OMXV index and stock prices of the Lithuanian stock market are taken and applied to a set of GARCH models. The main idea is to choose the best of the general autoregressive conditional heteroskedasticity models (GARCH) for OMXV index and all sectors. All models are ranged according to their ability to model stock price return. The main tendencies of the Lithuanian stock market are also analysed in this article by highlighting the leverage effect.

Suggested Citation

  • Deimante Teresiene, 2009. "Lithuanian stock market analysis using a set of Garch models," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(4), pages 349-360, August.
    • Handle: RePEc:taf:jbemgt:v:10:y:2009:i:4:p:349-360
    DOI: 10.3846/1611-1699.2009.10.349-360
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.3846/1611-1699.2009.10.349-360
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.3846/1611-1699.2009.10.349-360?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Steven A. Sharpe, 1999. "Stock prices, expected returns, and inflation," Finance and Economics Discussion Series 1999-02, Board of Governors of the Federal Reserve System (U.S.).
    2. Charlotte Christiansen & Angelo Ranaldo, 2007. "Realized bond—stock correlation: Macroeconomic announcement effects," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(5), pages 439-469, May.
    3. Grant McQueen, 2004. "Whence GARCH? A Preference-Based Explanation for Conditional Volatility," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 915-949.
    4. Black, Angela & Fraser, Patricia & Groenewold, Nicolaas, 2003. "U.S. stock prices and macroeconomic fundamentals," International Review of Economics & Finance, Elsevier, vol. 12(3), pages 345-367.
    5. Mr. Norbert Funke & Mr. Akimi Matsuda, 2002. "Macroeconomic News and Stock Returns in the United States and Germany," IMF Working Papers 2002/239, International Monetary Fund.
    6. Canto, Bea & Kräussl, Roman, 2006. "Stock market interactions and the impact of macroeconomic news: Evidence from high frequency data of European futures markets," CFS Working Paper Series 2006/25, Center for Financial Studies (CFS).
    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. Saralees Nadarajah & Emmanuel Afuecheta & Stephen Chan, 2015. "GARCH modeling of five popular commodities," Empirical Economics, Springer, vol. 48(4), pages 1691-1712, June.
    2. Iglesias, Emma M., 2015. "Value at Risk and expected shortfall of firms in the main European Union stock market indexes: A detailed analysis by economic sectors and geographical situation," Economic Modelling, Elsevier, vol. 50(C), pages 1-8.
    3. Yu Hsing, 2011. "Macroeconomic Variables and the Stock Market: the Case of Lithuania," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 3(1), pages 031-037, June.
    4. Imlak Shaikh & Puja Padhi, 2013. "Macroeconomic Announcements and the Implied Volatility Index: Evidence from India VIX," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(4), pages 417-442, November.

    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. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
    2. Nathan S. Balke & Mark E. Wohar, 2001. "Explaining stock price movements: is there a case for fundamentals?," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q III, pages 22-34.
    3. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets," MPRA Paper 54177, University Library of Munich, Germany.
    4. Peter Løchte Jørgensen & Domenico De Giovanni, 2010. "Time Charters with Purchase Options in Shipping: Valuation and Risk Management," Applied Mathematical Finance, Taylor & Francis Journals, vol. 17(5), pages 399-430.
    5. Piotr Fiszeder & Sebastian Rowinski, 2012. "Modeling relations between selected macroeconomic processes and the Warsaw Stock Exchange index," Ekonomia i Prawo, Uniwersytet Mikolaja Kopernika, vol. 10(3), pages 153-167, September.
    6. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    7. Ralph Chami & Thomas F. Cosimano & Connel Fullenkamp, 2001. "Capital Trading, Stock Trading, and the Inflation Tax on Equity," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 4(3), pages 575-606, July.
    8. Abdmoulah, Walid, 2010. "Testing the evolving efficiency of Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 25-34, January.
    9. Chiang, Min-Hsien & Huang, Hsin-Yi, 2011. "Stock market momentum, business conditions, and GARCH option pricing models," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 488-505, June.
    10. Kishore Joseph & Philip Garcia, 2018. "Intraday market effects in electronic soybean futures market during non-trading and trading hour announcements," Applied Economics, Taylor & Francis Journals, vol. 50(11), pages 1188-1202, March.
    11. Jingyi Liu, 2008. "Can a Lucas model with habit generate realistic conditional volatility in exchange rate returns?," Edinburgh School of Economics Discussion Paper Series 181, Edinburgh School of Economics, University of Edinburgh.
    12. Daniel Andrei & Bruce Carlin & Michael Hasler, 2019. "Asset Pricing with Disagreement and Uncertainty About the Length of Business Cycles," Management Science, INFORMS, vol. 67(6), pages 2900-2923, June.
    13. Elena Argentesi & Helmut Lütkepohl & Massimo Motta, 2010. "Acquisition of Information and Share Prices: An Empirical Investigation of Cognitive Dissonance," German Economic Review, Verein für Socialpolitik, vol. 11(3), pages 381-396, August.
    14. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    15. Liliam Sanchez Carrete & Vitor Corona & Rosana Tavares, 2016. "Impact of Number of Security Analysts in Liquidity of Brazilian Stocks," International Business Research, Canadian Center of Science and Education, vol. 9(11), pages 105-115, November.
    16. K. Cuthbertson & D. Nitzsche & S. Hyde, 2007. "Monetary Policy And Behavioural Finance," Journal of Economic Surveys, Wiley Blackwell, vol. 21(5), pages 935-969, December.
    17. Branston, Christopher B. & Groenewold, Nicolaas, 2004. "Investment and share prices: fundamental versus speculative components," The North American Journal of Economics and Finance, Elsevier, vol. 15(2), pages 199-226, August.
    18. repec:cpn:umkeip:2012:v3:p:153-167 is not listed on IDEAS
    19. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    20. Allard, Anne-Florence & Iania, Leonardo & Smedts, Kristien, 2020. "Stock-bond return correlations: Moving away from “one-frequency-fits-all” by extending the DCC-MIDAS approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    21. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.

    More about this item

    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:taf:jbemgt:v:10:y:2009:i:4:p:349-360. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TBEM20 .

    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.