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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, Publishing House "SINERGIA PRESS", vol. 29(1), pages 82-96.
  • Handle: RePEc:ris:apltrx:0204
    as

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    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(01), 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. 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.
    12. 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.
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    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

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