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

Frimpong, Joseph Magnus and Oteng-Abayie, Eric Fosu (2006): Modelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using GARCH Models.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Ghana Stock Exchange; developing financial markets; volatility; GARCH model
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets; G - Financial Economics > G1 - General Financial Markets > G10 - General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes

References

1. Hongyu, P. and Zhichao, Z., (2006), “Forecasting Financial Volatility: Evidence from Chinese Stock Market.” Working Paper in Economics and Finance, No. 06/02, University if Durham. 2. Piesse J and Hearn B (2002), Equity Market Integration versus Segmentation in Three Dominant Markets of the Southern African Customs Union: Cointegration and Causality Tests, Applied Economics, forthcoming 3. Osei, V., (2005), “Does the Stock Market Matter in Ghana? A Granger-Causality Analysis.” Working Paper, WP/BOG-05/13, Bank of Ghana. 4. Alagidede P and Panagiotidis T, 2006. "Calendar Anomalies in an Emerging African Market: Evidence from the Ghana Stock Exchange," Discussion Paper Series 2006_13, Economics Department, Loughborough University, revised Jun 2006. 5. Nelson, D.B 1991 ‘‘Conditional Heteroscedasticity in Asset Returns: A New Approach’’, Econometrica 55, p 703-708. 6. Eskandar, T., (2005), Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits. Working Paper # 0310, The Economic Research Forum , September. 7. Ogum, G., Beer, F., and Nouyrigat, G., (2005), “Emerging Equity Market Volatility An Empirical Investigation of Markets on Kenya and Nigeria.” Journal of African Business, 6: 1/2, 139 – 154, DOI: 10.1300/J156v06n01_08, ISSN: 1522-8916. 8. Mandelbrot, B., (1963), “The Variation of Certain Speculative Prices”, Journal of Business, 36, 394-419. 9. Fama, E., (1965), “The Behaviour of Stock Market Prices”, Journal of Business38 (1), 34-105. 10. Panagiotidis, T., (2002), “Testing the Assumption of Linearity”. Economics Bulletin, 3(29)1-9. 11. Dimson, E. and Marsh, P., (1990), “Volatility Forecasting without Data-Snooping”. Journal of Banking and Finance, 14, 399 – 421. 12. Bollerslev, T. (1986), Generalised Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 31, 307-27 13. Brooks, C. and Burke, S.P., 2003. Information Criteria for GARCH Model Selection: An Appplication to High Frequency Data, European Journal of Finance, 9:6, 557- 580. 14. Glosten, L. R; Jagannathan, R., and Runkle, D. E., (1993), “On the Relation between the Expected Value and the Volatility of the Nominal Excess Returns on Stocks.” Journal of Finance, 48(5), 1779-1791. 15. Brooks Chris, Introductory econometrics for finance, first edition, Cambridge University press, Cambridge, 2002 16. Brock, W.A., Dechert, W. and Scheinkman, H and LeBaron, B. (1996), “A test for Independence Based on the Correlation Dimension”. Econometric Reviews, 15, 197-235. 17. Panagiotidis, T., (2002), “Testing the Assumption of Linearity”. Economics Bulletin, 3(29)1-9. 18. Dimson, E. and Marsh, P., (1990), “Volatility Forecasting without Data-Snooping”. Journal of Banking and Finance, 14, 399 – 421.