Prediction of World Crude Oil Price with the Method of Missing Data

Xiaotong LI, Shaohui SUN, Taohua LIU

Abstract


As the fluctuation of oil price plays an important role in global political and economic situation, forecasting the price of oil is significant. In this paper, we analyze the data of the world crude oil price using ideas of treating with the missing data, i.e. we take the predictor as missing data and use the EM algorithm to establish time series model. We give the predictive values of weekly world crude oil price of January and February in 2011 using the data of 2009 and 2010. Meanwhile, we found that the method based on missing data is more effective than normal time series method by comparing the predictive value with reality data. In addition, this method is also applicable to the case that historical observations have missing data.
Key words: World Crude Oil Price; Forecast; Missing Data; EM Algorithm; Time Series

References


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