CBN Journal of Applied Statistics (JAS)


MGARCH, GO-GARCH, conditional heteroscedasticity, volatility, time-varying correlation


The study aimed at determining a set of superior generalized orthogonal-GARCH (GO-GARCH) models for forecasting time-varying conditional correlations and variances of five foreign exchange rates vis-à-vis the Nigerian Naira. Daily data covering the period 02/01/2009 to 19/03/2015 was used, and four estimators of the GO-GARCH model were considered for fitting the models. Forecast performance tests were conducted using the Diebold-Mariano (DM) and the model confidence set (MCS) tests procedures. The DM test indicates preference for the GO-GARCH model estimated with nonlinear least squares (NLS) estimator – denoted as GOGARCH-NLS, while the MCS test determined a set of superior models (SSM) which comprised of GO-GARCH-NLS and GOGARH model estimated by the method-of-moment, denoted as GO-GARCH-MM. These models were deemed best and adequate for forecasting of the five exchange rate dynamics.

Author Bio

The authors are from the Department of Statistics, University of Ibadan, Nigeria. E-mail: isenaUI@gmail.com and Central Bank of Nigeria.

Publication Title

CBN Journal of Applied Statistics







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