Business Review- A Journal of Business Administration Discipline, Khulna University, Volume: 11, Number: 1&2,January-December 2016, pp.9-19 (ISSN 1811-3788) Understanding the Investors’ Investment Decisions through Some Data Mining Tools- A Study in Dhaka Stock Exchange (DSE) 9 Understanding the Investors’ Investment Decisions through Some Data Mining Tools- A Study in Dhaka Stock Exchange (DSE) Md. Khashrul Alam 1 , S. M. Towhidur Rahman 2 , Afifa Khanom 3 Abstract Purpose: Decision making is the process of choosing a particular alternative from a number of alternatives. Decision making is very much important in investment in the stock market. As it is enormously sensitive, a wrong decision may put the investor back to the street. Modern scientific data mining tools can play important role in making investment decision in the stock market. The purpose of the study is to find out the effectiveness of investors’ decision in buying and selling stock and the efficiency of some data mining tools in aiding investor’s decision. Methodology: This paper used several data mining techniques such as beta, Chaikin money flow indicator (CMI) and Bollinger band to analyze investors’ decision in buying and selling stocks. Data for the study were taken both from primary and secondary sources specially, from website of Dhaka Stock Exchange. Findings: The result shows that in most cases majority of investors failed to take right decision in right time in terms of the estimation derived from data mining tools used in the study. It was also found that Bollinger band was found to be more efficient than CMI in making prediction. Key words: DSE, Beta Analysis, Chaikin’s Money Flow Indicator (CMI), Bollinger Bands (BB), Data mining. Introduction Stock market is an essential part of a country’s economy. Investors of the stock market invest their surplus money in the stock market mainly for achieving economic prosperity and for many other factors. The motivation of such investment is always beneficial for the country as it ensures healthy money flow between lenders and borrowers. The fundamental function of stock market is to arrange a secure, dependable and an efficient way of transferring funds between borrowers and lenders. To serve the basic function of stock market in Bangladesh, Dhaka stock Exchange (DSE) was established in the capital city. DSE becomes the best performing stock market of Asia in 2008 notwithstanding the global financial crisis (Asia Monitor, 2008). As a matter of fact, gains in DSE attracted investors of all level to invest in the stock market. However, the tempo could not be sustained and the market crashed in 2011. The index crossed 8500 points in 2010 and dramatically collapsed in the first quarter of 2011 and reached to 5500 points in October 2011. The continuous down movement of stock prices created panic among the investors in the market specially the individual investors. Financial market is in fact a complex, non-stationary, noisy, chaotic, nonlinear and dynamic system but it does not follow random walk process. The predictions of stock market price and its direction are quite challenging because a number of factors cause fluctuation in financial market movement including economic condition, political situation, traders’ expectations, catastrophes and other unexpected events (Ou and Wang, 2009). Within this inherent uncertainty in the stock market, investors usually invest based on their traditional knowledge. Sometimes they become gainer but sometimes this knowledge can’t help them turn just into a street beggar. In coping with such difficulty, data mining (or machine learning) techniques have been introduced and applied for this financial prediction which expects to aid investors to make better investment decisions and to prevent the extreme negative situation (ibid). So, in this study some data mining tools are employed and it is assessed whether they are more efficient than traditional decision making knowledge or not. 1 Professor, Business Administration Discipline, Khulna University, Email: khashru74@gmail.com 2 Associate Professor, Business Administration Discipline, Khulna University, Email: towhid_ku_97@yahoo.com 3 Independent Researcher, Business Administration Discipline, Khulna University.