Designing a Decision Support System Model for Stock Investment Strategy

• Main Authors: Chai, Chee Yong, Mohd Taib, Shakirah
• Format: Conference or Workshop Item
• Published: 2009
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utp.edu.my/4017/1/WCECS2009_pp312-316_StockDSS.pdf; http://eprints.utp.edu.my/4017/
• Institution: Universiti Teknologi Petronas

Investors face the highest risks compared to other form of financial investments when they invest in stock market.Their involvement in stock trading is mostly based on speculation where their aim is more to obtaining capital gain rather than earning dividend as their investment return over the long run. Many people had tried to predict the movement of share prices and beat the market but no one can really accurately predict the movement of a particular share prices for company listed in the stock exchange. There has been attempt from Information Technology (IT) professionals to exploit the stock price prediction area through the Artificial Intelligence(AI) approach. This paper presents the continuous effort to explore stock price and trend prediction from finance perspective as well as from the combination of two major IT areas which are AI and Data Mining (DM). These areas have been explored to design a hybrid stock price prediction model with relevant techniques into the Stock Price Analysis and Prediction activities. Index Terms—Artificial