Abstract

This study investigates the time series beaviour of daily stock
returns of four firms listed in the Nigerian Stock Market from 2nd
January, 2002 to 31st December, 2006, using three different models
of heteroscedastic processes, namely: GARCH (1,1), EGARCH (1,1) and
GJR-GARCH models respectively. The four firms whose share prices
were used in this analysis are UBA, Unilever, Guiness and Mobil. All
the return series exhibit leverage effect, leptokurtosis, volatility
clustering and negative skewness, which are common to most economic
financial time series. Except for Guiness, other series display
significant level of second-order autocorrelation, satisfying
covariance-stationary condition. These models were estimated
assuming a Gaussian distribution using Brendt-Hall-Hall-Hausman
(BHHH) algorithm's program in Eview software platform. The
estimation results reveal that the GJR-GARCH (1, 1) gives better fit
to the data and are found to be superior both in-sample and
out-sample forecasts evaluation.

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