High-Frequency CSI300 Spot and Futures Price Predictions via the Neural Network

The financial price index prediction is an important issue to market participants and policy makers. We focus on the price prediction problem for the CSI300 spot, its nearby futures, and its first distant futures using high-frequency 1 min data for the time frame from the launch of the futures market to about two years after all its constituent stocks becoming shortable, a period with continuously expanding trading of these financial indices. We employ the neural network to model these complex price time series and attempt to answer the following research questions: (1) can the prices be predicted by their own lags, and if so, how well; (2) can other two series help predictions of one series and by how much;…