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Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models

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  • Djahoué Mangblé Gérald

Abstract

Known as one of the key risk measures, volatility has attracted the interest of many researchers. These aim, in particular, to estimate and explain its evolution over time. Several results reveal that volatility is characterized, among other things, by its asymmetric variations (Chordia and Goyal 2006, Mele 2007, Shamila et al 2009, etc.). In this article, we seek to analyze and predict the volatility of the BRVM through these two indices. The data used are daily and start from the period from 04 January 2010 to 25 May 2016. We use three models of the GARCH family with asymmetric volatilities with different density functions. The results show a presence of asymmetry in the market yields. Also testifying to the presence of leverage in this market. The EGARCH model presents the best results in the analysis of the dynamics of market volatility behavior. JEL classification numbers: C22, C53, G17

Suggested Citation

  • Djahoué Mangblé Gérald, 2018. "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-4.
    • Handle: RePEc:spt:apfiba:v:8:y:2018:i:6:f:8_6_4
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    More about this item

    Keywords

    Stock Market Volatility; GARCH models; Asymmetric Variation; Leverage; Forecasting.;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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