n Annual Proceedings of the South African Statistical Association Conference - Volatility modelling using ARIMA-GARCH models in a hyperinflationary economic environment : the Zimbabwean experience

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The use of ARIMA-GARCH-type models for modelling volatility in a hyperinflationaty economic environment is investigated. The robustness and resilience of GARCH type models in forecasting conditional mean and volatility of monthly stock prices of eight counters listed on the Zimbabwe Stock Exchange (ZSE) over the period 1993 to 2004 under the assumption of a skewed Student - t distribution is tested. Symmetric and asymmetric GARCH type models are used. The results suggest that the monthly returns are characterized by an ARMA(0,1) process. This means that shocks to conditional mean dissipate after one period. Empirical results show that ARMA(0,1) - TARCH(1,1) model achieves the most accurate volatility forecasts followed by the ARMA(0,1) - GARCH(1,1) model. These results are useful in financial modeling in unstable and hyperinflationary economies.

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