Statistical analysis and predictions of fuel price distributions in the Philippines

Authors

Aimee B. Rarugal ⋅ PH National Institute of Physics, University of the Philippines Diliman
Ranzivelle Marianne Roxas-Villanueva ⋅ PH Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
Giovanni A. Tapang ⋅ PH National Institute of Physics, University of the Philippines Diliman

Abstract

We use interevent time statistics and Auto-Regressive Integrated Moving Average (ARIMA) modeling to analyze the diesel and unleaded prices of nine Philippine fuel companies. Results show that the prices typically change 6 days after a previous fuel price rollback or increase. Using ARIMA(1,1,1), the Jetti diesel price prediction has the best fit with respect to the original prices with Caltex as its covariate. For unleaded prices, Total has relatively the best fitting prediction, also with Caltex as the covariate. Evaluation of the goodness of predictions leads to the determination of influence factors on the fuel pricing of Philippine fuel companies.

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Issue

2014: Proceedings of the 32nd Samahang Pisika ng Pilipinas Physics Congress

Article ID

SPP2014-PA-04

Section

Poster Session PA

Published

2014-10-17

How to Cite

[1]

AB Rarugal, RM Roxas-Villanueva, and GA Tapang, Statistical analysis and predictions of fuel price distributions in the Philippines, Proceedings of the Samahang Pisika ng Pilipinas 32, SPP2014-PA-04 (2014). URL: https://proceedings.spp-online.org/article/view/1851.