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

Gbolahan Solomon Osho et al.

Journal of Applied Business and Economics2026https://doi.org/10.33423/jabe.v28i1.8077article
ABDC C
Weight
0.50

What the paper says

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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https://doi.org/https://doi.org/10.33423/jabe.v28i1.8077

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@article{gbolahan2026,
  title        = {{Monte Carlo-Based Forecasting and Optimization of Oil Price and Production: Evidence From Nigeria’s Petroleum Sector}},
  author       = {Gbolahan Solomon Osho et al.},
  journal      = {Journal of Applied Business and Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.33423/jabe.v28i1.8077},
}

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

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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