Analysis and Bayes statistical probability inference of crude oil price change point

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Jian Chai
  • Quanying Lu
  • Yi Hu
  • Shouyang Wang
  • Kin Keung Lai
  • And 1 others
  • Hongtao Liu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)271-283
Journal / PublicationTechnological Forecasting and Social Change
Volume126
Online published28 Sep 2017
Publication statusPublished - Jan 2018

Abstract

This paper introduces the Poisson distribution, power-law distribution, and logarithmic-normal distribution as the prior distributions to construct Bayes statistical probability inference model for the simulation of the monthly crude oil price change point trends. Based on basic statistical cognition and product partition model (PPM), the historical change points are defined, identified, and analyzed. The PPM-KM integration model is established by combining PPM model and K-means method to measure, cluster, and identify the posterior probability of change points. The appearance probabilities of change points under different scenarios are calculated and compared for single recursive probabilistic predictions. The results showed there were 37 significant change points during 1986–2015. In different time points, unbalance of market supply-demand structure, sudden geopolitical event, the US dollar index, and global economic development situation have become the main reasons for oil price catastrophes. The monthly crude oil price change point complied with the power-law distribution hypothesis. It provides a new analytical perspective and is beneficial to governments, enterprises and investors to understand the market trends, avoid investment risks and make the right investment decisions.

Research Area(s)

  • Bayesian methods, Change point, Crude oil price, K-means, Power-law distribution, PPM

Citation Format(s)

Analysis and Bayes statistical probability inference of crude oil price change point. / Chai, Jian; Lu, Quanying; Hu, Yi; Wang, Shouyang; Lai, Kin Keung; Liu, Hongtao.

In: Technological Forecasting and Social Change, Vol. 126, 01.2018, p. 271-283.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review