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On A New Exponentiated Error Innovation Distributions: Evidence of Nigeria Stock Exchange |
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PP: 321-331 |
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doi:10.18576/jsap/070209
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Author(s) |
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Samson Agboola,
Hussaini Garba Dikko,
Osebekwin Ebenezer Asiribo,
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Abstract |
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| This paper compared new error innovation distribution in estimating volatility models. A new error innovation distribution
called Exponentiated Generalized skewed student t distribution (EGSSTD) was developed and compared with the existing error
distributions using an empirical dataset of daily returns of Nigeria Stock Exchange (NSE) index return from 2007 to 2017. The result
of the stationarity Statistic shows that the data is stationary without transformation while the ARCH effect statistic using ADF statistic
shows the presence of heteroscedasticity. The estimate of the volatility models were significant with probability values at 0.01 for the
new error distribution and the existing distributions. The results obtained show that GARCH (1, 1) with EGSSTD error distribution
performed better than the other models having the least AIC value. In terms of forecasting performance, GARCH (1, 1) with ESSTD
error distribution outperformed other volatility models and error distributions with the least RSME. |
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