Statistical Models for Forecasting Petroleum Pump Prices in Kenya
[1]
Lawrence Areba Bichanga, Department of Mathematics and Physics, Kabarak University, Nakuru, Kenya.
This paper deals with predicting the mean Petroleum Pump Prices in Kenya by adopting time series statistical tools. In this study, data of mean Petroleum Pump Prices is taken for the period September 15, 2017 – October 14, 2017 to July 15, 2018 – August 14, 2018. Different Exponential smoothing tools and ARIMA models were taken into the consideration for the purpose of analysing the data and predicting the figures of future mean Petroleum Pump Prices in Kenya. Among the several models and tools best model were carved out by using the criteria like MAPE (Mean Absolute Percent Error) and RMSE (Root Mean Square Error) and AIC (Akaike Information Criterion). With the help of these criteria, on validation of the forecasts from these models, Double Exponential Smoothing models performed better than the ARIMA model for Mean Diesel and Kerosene pump prices. ARIMA model performed better than Double exponential Smoothing Model for Mean super Pump prices. These models may helpful to forecast the mean Petroleum Pump Prices in Kenya in upcoming years
Exponential Smoothing, ARIMA Model, Petroleum Pump Prices
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