Predictive Modeling of Ghana’s Private Sector Pensions Asset under Management Contribution Using ARIMA Model

Authors

  • Chinton Emmanuel Department of Statistics, University of Cape Coast, Ghana
  • Donkoh Kojo Isaac Financial Engineering, WorldQuant University, USA
  • Acquah Oware Nana Emmanuel Department of Economics and Finance, Youngstown State University, USA

DOI:

https://doi.org/10.54536/ajase.v4i1.5751

Keywords:

ARIMA, Asset Under Management (AUM), Pensions Contribution in Ghana, Private Sector

Abstract

This study applies an ARIMA (1,1,0) model to analyze the Private Sector Pension Assets Under Management (AUM) in Ghana. The model’s parameters and performance metrics were evaluated using SARIMAX results and the Dickey-Fuller Test for stationarity. The SARIMAX model demonstrated a significant autoregressive term (ar. L1 = 0.9693) and acceptable performance metrics (MAE = 5.99, RMSE = 13.89, MAPE = 23.97%), indicating a strong influence of past values on current AUM. The diagnostic tests suggested that residuals were not autocorrelated and approximately normally distributed. The Dickey-Fuller Test further confirmed the stationarity of the time series, with a test statistic of -5.3314 and a p-value of 4.7116e-06, allowing us to reject the null hypothesis of a unit root. Overall, the ARIMA (1,1,0) model provides a reliable framework for forecasting and analyzing the Private Sector Pension AUM in Ghana, supported by robust statistical validation.

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References

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Published

2025-10-06

How to Cite

Chinton, E., Kojo Donkoh, I., & Nana Oware Acquah, E. (2025). Predictive Modeling of Ghana’s Private Sector Pensions Asset under Management Contribution Using ARIMA Model. American Journal of Applied Statistics and Economics, 4(1), 112–118. https://doi.org/10.54536/ajase.v4i1.5751