MODELING BRENT OIL PRICE WITH MARKOV CHAIN PROCESS OF THE FUZZY STATES

Abstract

Purpose -  The rapid change of crude oil price in the international market has attacted several investors into examining price fluctuations. The estimation regarding to the exact monthly price of the brent oil has always been a diffucult task in the business sector.  

Methodology -  In this study, the directions of the monthly Brent oil prices from January 2003 to January 2017are analyzed using the Markov Chains of Fuzzy States technique. In the first instance, the data are classified into twenty-one fuzzy states, and then calculated the probability transition matrix of the fuzzy states for the given period.

Findings- The directions of the monthly Brent oil prices are analyzed with transition matrix. Next  the steady condition of the Brent oil return is obtained. These results give valuable information to decision makers regarding the investment opportunities of Brent oil for the short and long term marketing strategies.

Conclusion- In crucial months, when a monthly return increases or decreases significantly, the proceeding month’s expected return also increase or decreases significantly. The proposed model can be used to estimate short term returns (one day) and also employing several fuzzy sets may give more investment opportunities. 

Keywords

• Brent oil price,Markov chains,Fuzzy logic,Fuzzy states of Markov chains

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