Share price time series forecasting for effective supply chain information exchange

This article presents the performance analysis of share price prediction using neural network and support vector machine models. The purpose of the research work is to evaluate the best model for the time series forecasting and share price performance prediction of a leading green coffee export company in the Indian stock market, which would in turn help the various stakeholders of the Indian green coffee supply chain, in taking their important business decisions to improve the information exchange among different echelons of the supply chain. The share price data collected was trained and validated using multilayer perceptron, general regression neural network and support vector machine models. The findings and comparative analysis reveals the better performance of support vector machine among other methods.