IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0204.html
   My bibliography  Save this article

Using news analytics data in GARCH models

Author

Listed:
  • Sidorov, Sergei

    (Saratov State University, Russia)

  • Date, Paresh

    (Brunel University, London)

  • Balash, Vladimir

    (Saratov State University, Russia)

Abstract

In this paper we analyze the impact of extraneous sources of information (viz. news and trade volume) on stock volatility by considering some augmented GARCH models. We suppose that trading volume can be considered as a proportional proxy for information arrivals to the market. Then we will consider the daily number of press releases on a stock (news intensity) as an alternative explanatory variable in the basic equation of GARCH model. We will show that the GARCH(1,1) model augmented with volume does remove GARCH and ARCH effects for the most of the companies, while the GARCH(1,1) model augmented with news intensity has difficulties in removing the impact of log return on volatility.

Suggested Citation

  • Sidorov, Sergei & Date, Paresh & Balash, Vladimir, 2013. "Using news analytics data in GARCH models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 82-96.
    • Handle: RePEc:ris:apltrx:0204
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2013_1_82-96.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miyakoshi, Tatsuyoshi, 2002. "ARCH versus information-based variances: evidence from the Tokyo Stock Market," Japan and the World Economy, Elsevier, vol. 14(2), pages 215-231, April.
    2. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    3. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    4. Vanitha Ragunathan & Albert Peker, 1997. "Price variability, trading volume and market depth: evidence from the Australian futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 7(5), pages 447-454.
    5. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. 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.
    8. Gust Janssen, 2004. "Public information arrival and volatility persistence in financial markets," The European Journal of Finance, Taylor & Francis Journals, vol. 10(3), pages 177-197.
    9. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    10. 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.
    11. Arago, Vicent & Nieto, Luisa, 2005. "Heteroskedasticity in the returns of the main world stock exchange indices: volume versus GARCH effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 271-284, July.
    12. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    13. Kalev, Petko S. & Liu, Wai-Man & Pham, Peter K. & Jarnecic, Elvis, 2004. "Public information arrival and volatility of intraday stock returns," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1441-1467, June.
    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. Alpha Basweti Kenyatta & Antony Ngunyi & Anthony Gichuhi Waititu, 2020. "News Classification using Support Vector Machine to Model and Forecast Volatility," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(1), pages 1-1.

    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. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    2. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    3. Sam Howison & David Lamper, 2001. "Trading volume in models of financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(2), pages 119-135.
    4. Madarassy Akin, Rita, 2003. "Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets," Santa Cruz Center for International Economics, Working Paper Series qt1n04g31b, Center for International Economics, UC Santa Cruz.
    5. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    6. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    7. Kalev, Petko S. & Liu, Wai-Man & Pham, Peter K. & Jarnecic, Elvis, 2004. "Public information arrival and volatility of intraday stock returns," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1441-1467, June.
    8. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2006. "Stochastic Volatility, Trading Volume, and the Daily Flow of Information," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1551-1590, May.
    9. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Liquidity, surprise volume and return premia in the oil market," Energy Economics, Elsevier, vol. 77(C), pages 93-104.
    10. Madarassy Akin, Rita, 2003. "Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets," Santa Cruz Department of Economics, Working Paper Series qt1n04g31b, Department of Economics, UC Santa Cruz.
    11. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    12. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.
    13. 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.
    14. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    15. Robert F. Engle & Martin Klint Hansen & Asger Lunde, 2012. "And Now, The Rest of the News: Volatility and Firm Specific News Arrival," CREATES Research Papers 2012-56, Department of Economics and Business Economics, Aarhus University.
    16. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    17. Ho, Kin-Yip & Zheng, Lin & Zhang, Zhaoyong, 2012. "Volume, volatility and information linkages in the stock and option markets," Review of Financial Economics, Elsevier, vol. 21(4), pages 168-174.
    18. Yadav, Pradeep K., 1992. "Event studies based on volatility of returns and trading volume: A review," The British Accounting Review, Elsevier, vol. 24(2), pages 157-184.
    19. Zhang, Yongjie & Feng, Lina & Jin, Xi & Shen, Dehua & Xiong, Xiong & Zhang, Wei, 2014. "Internet information arrival and volatility of SME PRICE INDEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 70-74.
    20. repec:lan:wpaper:3326 is not listed on IDEAS
    21. repec:lan:wpaper:3050 is not listed on IDEAS
    22. repec:lan:wpaper:3048 is not listed on IDEAS
    23. Eric Girard & Mohammed Omran, 2009. "On the relationship between trading volume and stock price volatility in CASE," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 5(1), pages 110-134, February.

    More about this item

    Keywords

    stock volatility modeling; GARCH models;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:ris:apltrx:0204. 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: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    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.