Gbolahan Solomon Osho, Oluwagbemiga Ojumu, Sudhir Tandon, Bolaji Oloyede

Monte Carlo-Based Forecasting and Optimization of Oil Price and Production: Evidence From Nigeria’s Petroleum Sector

Introduction

Monte carlo-based forecasting and optimization of oil price and production: evidence from nigeria’s petroleum sector. Forecast and optimize Nigeria's oil price and production using Monte Carlo simulations & ARIMA. Analyze Bonny Light crude data (2000-2024) to predict trends, revenue swings, and inform fiscal planning.

Abstract

This study employs a Monte Carlo simulation framework integrated with ARIMA-based time series analysis to forecast oil price and production trends in Nigeria’s petroleum sector. Using historical Bonny Light crude and production data (2000–2024), the model generated 10,000 stochastic iterations to capture volatility and uncertainty. Results indicate average forecasts of $76 per barrel and 1.71 million barrels per day, within 95% confidence bounds. Scenario analysis revealed monthly revenue swings from $2.4 to $4.9 billion. These findings emphasize the importance of probabilistic forecasting for fiscal planning and investment strategies in resource-dependent economies.

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