Identification of Robust Garch Models with Symmetric and Asymmetric Process with the use of Beta Volatility Coefficient and Model Accuracy Measure

The goal of this study was to identify a reliable GARCH model for modeling and forecasting each economic variable in Nigeria, including the price crude oil, consumer index, exchange rate, inflation rate. Monthly secondary data simulated sets were that used. Between January 2004 December 2020, are covered. Beta Volatility Coefficient (BVC) proposed detecting volatility research data. Using method called Model Accuracy Measure (MAM) different sample sizes: 50, 100, 150, 200, robust models found. Leverage impact there, according Asymmetric models' results. All variables have statistically significant value value. Inflation rate series is 11% more volatile than Crude Oil Price Exchange series, when size large, Consumer Index 55% results BVC Symmetric at various sizes (200). asymmetric "E-GARCH (1, 1) Model," symmetric "GARCH-M "GARCH Model" identified prediction Rate respectively. In general, outperformed Index, which an improvement over earlier research. Rate. For variable, found utilized create predictions between 2022 2024. expected ranges oil $31.82 ±1.08, N14.65 ±0.03, N/$756.76 ±53.84, index N2.26 ±0.11.