Abstract:
While there are a number of finance methods (fundamental analysis, technical analysis, contrarians' theory, risks
management,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 systematic
method (i.e. an IDSS system) to take advantage of and to optimize existing and newly proposed methods in order to
obtain better investment performance, through identification and classification of Positive, Neutral and Negative
investment opportunity ranges and related risks. This IDSS system will be mainly based on Turning Point Model and
Optimized AutoSplit method, which help find hidden investment opportunities and risk variables, particularly a stock's
unique key methodology is to use Decision Tree theory with finance knowledge. The IDSS system will be
built on top of F-trade platform which has been already developed by VTS Data Mining team and has a RDP
structure with agent-based distributed expert systems. Initial system evaluation shows that the system successfully
identified investment opportunity ranges, outperforming the benchmark index and other systems.
