Designing a decision support system for stock exchange selection based on serious games simulation


A model for designing of decision support system is a simulation that induces reality and uses different models to describe the complex reality. It also concerns uncertainty and can help users to achieve a conceptual and detailed description of the reality. Serious game is being used as a tool for developing model for a long time. Producing serious games simulation environments is one of the best options in data collection, trial and error, and learning and decision-making for the investment markets that rapid change of the rate increases the risk. A virtual system will provide better aid by using actual data foe a better management of the financial resources and offer options for users at every level of decision. Entering the stock market is possible for everyone but the possibility of selecting a stock portfolio that results in achieving a good profit is very difficult and hard, due to rapidly changing customer markets is becoming more difficult. That is it's a high-risk environment for investors. Indeed people do not have sufficient experience and training in this field. Indeed all people don't have sufficient experience and training in this field. The goal is designing a simulated environment that is similar to the stock for the brokers and enthusiasts to help them to choose an appropriate portfolio. Moreover it should have an interactive graphical environment that even novice users can find the necessary training in this area. Creating a Simulation environment in serious games requires rebuilding and finding the principles and a framework that not only involves the world standard hay accepted by experts in the field but also, according to Iran's investment conditions, becomes localized and in practice, will be efficient.

DOI Code: 10.1285/i2037-3627v5n1p83

Keywords: Decision support systems, serious gaming simulation, neural network, fuzzy neural networks, Java, MATLAB.

Full Text: pdf

Creative Commons License
This work is licensed under a Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia License.