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The effects of trading activity on market volatility

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  • Giampiero Gallo
  • Barbara Pacini

Abstract

The paper re-examines the question of excessive implied persistence of volatility estimates when GARCH type models are used. Ten actively traded US stocks are considered and as already established in the literature, when volume traded is inserted in the GARCH (1, 1) or (EGARCH 1, 1) models for returns, the estimated persistence is decreased. Since volume is affected also by within-the-day price movements and hence is not weakly exogenous relative to returns, alternative proxies for trading activities are suggested. It is concluded that the difference between the opening price and the closing price of the previous day accounts also for most of the persistence in the autoregressive conditional heteroskedasticity.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 6 (2000)
Issue (Month): 2 ()
Pages: 163-175

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Handle: RePEc:taf:eurjfi:v:6:y:2000:i:2:p:163-175

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Related research

Keywords: Persistence Market Efficiency;

References

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Citations

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Cited by:
  1. Alsubaie, Abdullah & Najand, Mohammad, 2009. "Trading volume, time-varying conditional volatility, and asymmetric volatility spillover in the Saudi stock market," Journal of Multinational Financial Management, Elsevier, Elsevier, vol. 19(2), pages 139-159, April.
  2. Brajesh Kumar & Priyanka Singh & Ajay Pandey, 2010. "The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market," Working Papers id:2379, eSocialSciences.
  3. Hasan Baklaci & Adnan Kasman, 2006. "An Empirical Analysis of Trading Volume and Return Volatility Relationship in The Turkish Stock Market," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 6(2), pages 115-125.
  4. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
  5. Henryk GURGUL & Tomasz WÓJTOWICZ, 2006. "Long Memory on the German Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, Charles University Prague, Faculty of Social Sciences, vol. 56(09-10), pages 447-468, September.
  6. Brian M. Lucey, 2005. "Does volume provide information? Evidence from the Irish Stock Market," Applied Financial Economics Letters, Taylor and Francis Journals, Taylor and Francis Journals, vol. 1(2), pages 105-109, March.
  7. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, Elsevier, vol. 25(3), pages 238-254, September.
  8. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, School of Economics and Management, University of Aarhus.
  9. Henryk Gurgul & Paweł Majdosz & Roland Mestel, 2007. "Price–volume relations of DAX companies," Financial Markets and Portfolio Management, Springer, Springer, vol. 21(3), pages 353-379, September.
  10. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
  11. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63.
  12. Constantinos Katrakilidis & Athanasios Koulakiotis, 2006. "The Impact of Stock Exchange Rules on Volatility and Error Transmission -- The Case of Frankfurt and Zurich Cross-Listed Equities," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 321-338, November.
  13. Guillermo Benavides, 2010. "Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective," Working Papers 2010-12, Banco de México.
  14. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, . "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
  15. Lucía Cuadro Sáez & Manuel Moreno, 2007. "GARCH Modeling of Robust Market Returns," Kiel Advanced Studies Working Papers, Kiel Institute for the World Economy 440, Kiel Institute for the World Economy.
  16. 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, Emerald Group Publishing, vol. 5(1), pages 110-134, February.
  17. Henryk Gurgul & Tomasz Wojtowicz, 2006. "Long-run properties of trading volume and volatility of equities listed in DJIA index," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, Wroclaw University of Technology, Institute of Organization and Management, vol. 3, pages 29-56.
  18. Bohl, Martin T. & Henke, Harald, 2003. "Trading volume and stock market volatility: The Polish case," International Review of Financial Analysis, Elsevier, vol. 12(5), pages 513-525.
  19. Müller, Christian, 2012. "A new interpretation of known facts: The case of two-way causality between trading and volatility," Economic Modelling, Elsevier, vol. 29(3), pages 664-670.
  20. Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.

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