Decision-making system for stock exchange market using artificial emotions

Abstract

This work presents an autonomous affective decision-making system devoted to the support of decision-making processes in the stock exchange market domain. The current proposals of intelligent systems and automated platforms to support operations in the stock exchange market use strongly analytical indicators. However, the above represents an important limitation because all decisions made by these proposals must be defined and constantly monitored by human investors. The use of artificial emotions allows the system to configure its own notion of confidence based on the correlation between investment decisions made and the associated emotional reactions. The above allows the system to increase the degree of autonomy in its decisions by providing a mechanism that is more adaptive to changing stock exchange market conditions. In this way, the delegation of decision-making by human investors is promoted. A definition of an artificial emotional decision-making system was implemented and applied to real data of the New York Stock Exchange Market. The results are promising and suggest that using artificial emotions in autonomous decision-making systems can represent an important future research area, improving the effectiveness of each decision.