Simulating the linguistic variables interactions in capital market development process using fuzzy inference system in a system dynamic context

This research aims at simulating the interactions of linguistic variables affecting market capitalization of capital market. In this regard, the dynamic model of the research has been designed by using a system dynamics approach and, in order to reflect investor’s mentality, the fuzzy inference system has been merged with system dynamics methodology. In this framework, the fuzzy membership functions of variables such as Market Efficiency, Market Manipulation, Investor’s Knowledge and Culture, Market Trust, and Investor’s Sentiment has been defined and Using Vensim DSS to simulate the scenarios, the validity of the model has been tested under systemic and statistical tests., This research is a applied study with an exploratory mixed method framework that has been conducted during 1386 to 1404. The results show that simultaneous change in endogenous variables, results in faster and greater change in market capitalization than distinct change in each of this variables. Changing the Market Efficiency, Investor’s Knowledge and Culture, and Market Manipulation in the demanded way will increase the market capitalization by 77% in the comparison with base run simulation values. The results of sensitivity analysis shows that market capitalization is more sensitive to simultaneous change of endogenous variables than the distinct changes of each of these variables.