International records / OpenAlex research

Modeling Nigerian Crude Oil Prices: Comparative Evaluation of Linear, Volatility, and Deep Learning Approaches

The study focuses on determining the prediction performance of autoregressive integrated moving average (ARIMA), generalized autoregressive conditional heteroskedasticity (GARCH) and long short-term memory (LSTM) models of Nigerian crude oil prices. The comparisons among traditional linear models, volatility-based models, and deep learning approaches were done using monthly data from January 1946 to June 2025. Based on the outcomes, the ARIMA (1,1,0) model produces a fairly good linear fit for the data. However, it has relatively high prediction errors, with an MSE equal to 590.87, RMSE equal …