An Investment decision support system (IDSS) for identifying positive, neutral and negative investment opportunity ranges with risk control in stock markets

While there are a number of finance methods (fundamental analysis, technical analysis, contrarians' theory, risksmanagement,etc) used in stock markets to help make investment decisions, they have different strengths and weakness.It is observed that these different finance methods are not being integrated by existing technologies in a systematic way,thus their performance for identifying investment opportunities is limited. In this research, I propose a systematicmethod (i.e. an IDSS system) to take advantage of and to optimize existing and newly proposed methods in order toobtain better investment performance, through identification and classification of Positive, Neutral and Negativeinvestment opportunity ranges and related risks. This IDSS system will be mainly based on Turning Point Model andOptimized AutoSplit method, which help find hidden investment opportunities and risk variables, particularly a stock'sunique key methodology is to use Decision Tree theory with finance knowledge. The IDSS system will bebuilt on top of F-trade platform which has been already developed by VTS Data Mining team and has a RDPstructure with agent-based distributed expert systems. Initial system evaluation shows that the system successfullyidentified investment opportunity ranges, outperforming the benchmark index and other systems.