Cognitive Intelligence based Expert System for Predicting Stock Markets using Prospect Theory

Objectives: Design of Expert Systems to assist the investors in stock markets is gaining significant importance in the area of financial investments. The rapid explosion of globalization has armed the investors with the ability to invest their money in the stock markets across the globe. Thus the need for rationalized decision making by psychologically analyzing the behaviour of stockholders has become inevitable. Method/Analysis: This concept of behavioural economics integrated the emotional, intellectual and socio-economic factors in decoding the complex economic decisions. Under these circumstances, the traditional finance theory which highlights the rational and calculative decision making setup, contradicts with the new behavioural finance theory which is marked by irrational and high uncertainty based resolutions, that involves cognitive and emotional errors. In the light of these factors, designing a suitable expert system to assist the investors by combining the financial factors, investor sentiments and the information technology using Prospect Theory is the need of the day and this paper proposes to design and develop an efficient expert system using C#.NET. Findings: The stock values of leading banks like State Bank of India, Indian Bank, Indian Overseas Bank and Punjab National Bank were chosen as the experimental data sources. The experimental results clearly show that a relatively low error levels have been achieved when the expert system utilizes the Prospects to predict the results. Applications/Improvement: The value of normalized mean square error has been reduced to 1.1028 from the pre-prospect value of 1.1510 with respect to the share value of State Bank of India and similar results have been predicted for the other bank shares