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Markov chain and oil import opportunity decision
ZHANG Chuan ping, CHEN Hong jie, YAN Xue ping, ZHAO Rui rui, ZHANG Qing, ZHANG Yan xia
(College of Economic Administration in China University of Petroleum, Dongying 257061, China)
Abstract:
By summarizing oil prediction models, the oil price dynamic progress was regarded as markov chain. The states transition probability of markov chain was calculated by the mathematical statistics method. According to markov chain 's property, the long runs steady probability was obtained on the basis of state transition probability. The dynamic programming techniques was used to get opportune decisions of oil importing. The practical opportune decisions of oil importing can be done by this method. The results show that this decision method could avoid "to buy price rising instead of dropping", be simple and convenient, and improve the data use factor.
Key words:  oil price  markov chain  steady probability  dynamic programming  import policy