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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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 593.

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Date of creation: 07 Oct 2006
Date of revision: 07 Oct 2006
Handle: RePEc:pra:mprapa:593

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Keywords: Ghana Stock Exchange; developing financial markets; volatility; GARCH model;

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References

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  1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  2. Theodore Panagiotidis, 2002. "Testing the assumption of Linearity," Economics Bulletin, AccessEcon, vol. 3(29), pages 1-9.
  3. Paul Alagidede & Theodore Panagiotidis, 2006. "Calendar Anomalies in an Emerging African Market: Evidence from the Ghana Stock Exchange," Discussion Paper Series, Department of Economics, Loughborough University 2006_13, Department of Economics, Loughborough University, revised Jun 2006.
  4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, American Finance Association, vol. 48(5), pages 1779-1801, December.
  5. Chris Brooks & Simon Burke, 2003. "Information criteria for GARCH model selection," The European Journal of Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 9(6), pages 557-580.
  6. Dimson, Elroy & Marsh, Paul, 1990. "Volatility forecasting without data-snooping," Journal of Banking & Finance, Elsevier, Elsevier, vol. 14(2-3), pages 399-421, August.
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Cited by:
  1. Emenike, Kalu O., 2010. "Modelling Stock Returns Volatility In Nigeria Using GARCH Models," MPRA Paper 22723, University Library of Munich, Germany.

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