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Volatility Modelling and Trading Volume of the CARS Equity Indices

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Advances in Cross-Section Data Methods in Applied Economic Research (ICOAE 2019)

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Abstract

In this study, the effect and significance of new information on the volatility of different markets (developed vs. emerging) are considered. The effect of new information on volatility is tested in a GARCH framework. Data for four commodity-based equity markets is used for the analysis. The Akaike and Schwarz information criterion are used to the fitted univariate GARCH models, and the root-mean-square error and mean absolute error are used to compare the forecasting performance. Empirical results show that new information (trading volume) does improve forward-looking estimates of volatility. There is not a significant difference in terms of the effect of new information in volatility modelling when developed and emerging markets are considered.

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Author information

Authors and Affiliations

  1. Department of Finance and Investment Management, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa

    Niel Oberholzer & Chalté Venter

Authors
  1. Niel Oberholzer
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  2. Chalté Venter
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Corresponding author

Correspondence to Niel Oberholzer .

Editor information

Editors and Affiliations

  1. Department of Economics, University of Western Macedonia, Kastoria, Greece

    Nicholas Tsounis

  2. Department of Economics, University of Western Macedonia, Kastoria, Greece

    Aspasia Vlachvei

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Oberholzer, N., Venter, C. (2020). Volatility Modelling and Trading Volume of the CARS Equity Indices. In: Tsounis, N., Vlachvei, A. (eds) Advances in Cross-Section Data Methods in Applied Economic Research. ICOAE 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-38253-7_21

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