Forecasting Crude Oil Price and Stock Price by Jump Stochastic Time Effective Neural Network Model

Abstract EN

The interacting impact between the crude oil prices and the stock market indicesin China is investigated in the present paper, and the corresponding statisticalbehaviors are also analyzed.

The database is based on the crude oil prices of Daqing and Shengli in the 7-year period from January 2003 to December 2009 and alsoon the indices of SHCI, SZCI, SZPI, and SINOPEC with the same time period.

Ajump stochastic time effective neural network model is introduced and applied toforecast the fluctuations of the time series for the crude oil prices and the stockindices, and we study the corresponding statistical properties by comparison.

Theexperiment analysis shows that when the price fluctuation is small, the predictivevalues are close to the actual values, and when the price fluctuation is large, thepredictive values deviate from the actual values to some degree.

Moreover, thecorrelation properties are studied by the detrended fluctuation analysis, and theresults illustrate that there are positive correlations both in the absolute returns ofactual data and predictive data.