Forecasting System by Smoothing Method For Trading in Stock Exchange of Thailand (SET)

Abstract

The convergence of information technology and data science innovation is developed using a computational base as a stock price forecasting system offers trading in Stock Exchange of Thailand (SET). Traditionally, a particular circumstance of each business may influence different patterns in time-series of stock price, so it requires different techniques to forecast the prices. This paper presents the forecasting system which employs three techniques of smoothing methods: moving average, weighted moving average and exponential smoothing. All techniques provide the process to forecast five types of trading prices: open price, closed price, maximum price, minimum price and average in real-time price. This system is flexibly designed and allows investors to be able to specify the input conditions for the particular predictable techniques in conformance to each technique instead of using the programmer restriction. The result of the system implementation provides descriptive information, including reports of market situation and diagnosis of predictable prices so as to serve investors for consideration and decision for investment. This contribution would aim to promote economic growth by stock markets as a whole.