Exponential Smoothing Methods for Detection of the Movement of Stock Prices

Abstract

Business Intelligence is a set of processes, architecture and technologies that convert raw data into meaningful information. BI has a direct impact on an organization’s strategic statistical and operational business decisions. In BI one of the most interesting areas is time series data analysis to predict are stock prices. Prediction and analysis of stock market data has got an important role in today’s economy. The aim of this paper is to predict the daily previous closing stock prices of the major tech giants of NSE (i.e. HCLTECH and TCS), using information from the historical data with the help Exponential Smoothing Methods. The historical stock prices of the stated companies for three years will be used for the training and testing of the methods. It is found that Holt-Winter’s method of exponential smoothing the given the best results out of the other exponential smoothing methods.