Original Research

Volatility forecasting and value-at-risk estimation in emerging markets: the case of the stock market index portfolio in South Africa

Lumengo Bonga-Bonga, George Mutema
South African Journal of Economic and Management Sciences | Vol 12, No 4 | a184 | DOI: https://doi.org/10.4102/sajems.v12i4.184 | © 2011 Lumengo Bonga-Bonga, George Mutema | This work is licensed under CC Attribution 4.0
Submitted: 20 April 2011 | Published: 21 April 2011

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Lumengo Bonga-Bonga, University of Johannesburg, South Africa
George Mutema, University of Johannesburg, South Africa

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Accurate modelling of volatility is important as it relates to the forecasting of Value-at-Risk (VaR). The RiskMetrics model to forecast volatility is the benchmark in the financial sector. In an important regulatory innovation, the Basel Committee has proposed the use of an internal method for modelling VaR instead of the strict use of the benchmark model. The aim of this paper is to evaluate the performance of RiskMetrics in comparison to other models of volatility forecasting, such as some family classes of the Generalised Auto Regressive Conditional Heteroscedasticity models, in forecasting the VaR in emerging markets. This paper makes use of the stock market index portfolio, the All-Share Index, as a case study to evaluate the market risk in emerging markets. The paper underlines the importance of asymmetric behaviour for VaR forecasting in emerging markets’ economies.


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