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Modelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using GARCH Models

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  • Frimpong, Joseph Magnus
  • Oteng-Abayie, Eric Fosu

Abstract

This paper models and forecasts volatility (conditional variance) on the Ghana Stock Exchange using a random walk (RW), GARCH(1,1), EGARCH(1,1), and TGARCH(1,1) models. The unique ‘three days a week’ Databank Stock Index (DSI) is used to study the dynamics of the Ghana stock market volatility over a 10-year period. The competing volatility models were estimated and their specification and forecast performance compared with each other, using AIC and LL information criteria and BDS nonlinearity diagnostic checks. The DSI exhibits the stylized characteristics such as volatility clustering, leptokurtosis and asymmetry effects associated with stock market returns on more advanced stock markets. The random walk hypothesis is rejected for the DSI. Overall, the GARCH (1,1) model outperformed the other models under the assumption that the innovations follow a normal distribution.

Suggested Citation

  • Frimpong, Joseph Magnus & Oteng-Abayie, Eric Fosu, 2006. "Modelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using GARCH Models," MPRA Paper 593, University Library of Munich, Germany, revised 07 Oct 2006.
    • Handle: RePEc:pra:mprapa:593
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    References listed on IDEAS

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    Cited by:

    1. Ananda Chatterjee & Hrisav Bhowmick & Jaydip Sen, 2022. "Stock Volatility Prediction using Time Series and Deep Learning Approach," Papers 2210.02126, arXiv.org.
    2. Kumar Arya & Sahoo Jyotirmayee & Sahoo Jyotsnarani & Nanda Subhashree & Debyani Devi, 2024. "Exploring Asymmetric GARCH Models for Predicting Indian Base Metal Price Volatility," Folia Oeconomica Stetinensia, Sciendo, vol. 24(1), pages 105-123.
    3. Aastha KHERA & Dr. Miklesh Prasad YADAV, 2020. "Predicting the volatility in stock return of emerging economy: An empirical approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(625), W), pages 233-244, Winter.
    4. Emenike, Kalu O., 2010. "Modelling Stock Returns Volatility In Nigeria Using GARCH Models," MPRA Paper 22723, University Library of Munich, Germany.
    5. George Amfo-Antiri & Edward Quansah, 2017. "Cointegration of Stock Prices and Domestic Portfolio Diversification Opportunities: Evidence from the Ghana Stock Exchange," Applied Economics and Finance, Redfame publishing, vol. 4(5), pages 78-93, September.
    6. Ntebogang Dinah Moroke, 2015. "An Optimal Generalized Autoregressive Conditional Heteroscedasticity Model for Forecasting the South African Inflation Volatility," Journal of Economics and Behavioral Studies, AMH International, vol. 7(4), pages 134-149.

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    More about this item

    Keywords

    Ghana Stock Exchange; developing financial markets; volatility; GARCH model;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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