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A Generalized Autoregressive Conditional Heteroskedasticity Examination of the Relationship between Trading Volume and Conditional Volatility in the Tunisian Stock Market: Evidence for the Information Flow Paradigm

Author

Listed:
  • Fethi Belhaj

    (Faculty of Economics and Management Sciences of Nabeul, Tunisia,)

  • Ezzeddine Abaoub

    (College of Administrative and Financial Studies, Taif University, Kingdom of Saudi Arabia.)

Abstract

This paper empirically examines the relationship between trading volume and conditional volatility of returns in the Tunisian stock market within the framework of the mixture of distribution hypothesis (MDH) and the sequential information arrival hypothesis (SIAH). Through this study, we especially aim to test the volatility persistence degree without volume, with contemporaneous volume, and with lagged volume. Our empirical analysis is based on daily data related to the 43 most active and dynamic securities traded from January 2, 2008 to June 29, 2012. Our daily analysis reveals several results. Firstly, we confirm the strong positive relationship between trading volume and returns conditional volatility issued from generalized autoregressive conditional heteroskedasticity (GARCH (1,1)) model. Secondly, according to the theoretical predictions of the MDH, we show that including contemporaneous trading volume in the conditional variance equation significantly reduces volatility persistence. Thirdly, through the addition of the lagged volume in the conditional variance equation, we show that volatility persistence remains in the whole at a high level and close to that obtained from the GARCH (1,1) model without trading volume, and also at a higher level than that resulting from the addition of the contemporaneous volume. Our results thus do not support the implications of the SIAH.

Suggested Citation

  • Fethi Belhaj & Ezzeddine Abaoub, 2015. "A Generalized Autoregressive Conditional Heteroskedasticity Examination of the Relationship between Trading Volume and Conditional Volatility in the Tunisian Stock Market: Evidence for the Information," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 354-364.
    • Handle: RePEc:eco:journ1:2015-02-05
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    References listed on IDEAS

    as
    1. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    2. 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, vol. 19(2), pages 139-159, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Trading Volume; Conditional Volatility; Mixture of Distribution Hypothesis; Sequential Information Arrival Hypothesis; Generalized Autoregressive Conditional Heteroskedasticity; Volatility Persistence; Information flow;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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