The Agent-based modeling of stockholders? behavior in Iranian capital market
One of the main concerns of the market regulators is the prediction of the effects of these new strategies on the market due to the heterogeneity of the agents, rational boundary and behavioral factors in the investors’decision making. The Iranian stock market has always been fluctuating; therefore,awareness of the effects of strategies before they are implementedwill help regulators to market more effectively. The main objective of this research is to create an artificial market according to the Iranian stock market so that different scenarios can be simulated.
One of these emerging areas, which emphasizes the impact of social sciences, cognitive sciences and behavioral sciences on operational research, is "Behavioral Operations Research" that helps us solve real-world problems.In this research, considering modeling based onagent-based capabilities, shareholders’ capabilities, bonds including different types of stocks and risk-free papers, and trading rules.
In this artificial market in each trading period, in accordance with the trading strategy and learning procedures, the agents intendto buy and sell. Eventually they worked as the market makers, in accordance with the auction mechanism, and began to execute orders and perform clearing and settlement operations. In order to examine the validity of the model, the statistical output of this market wasadapted to the statistical characteristics of the financial markets and, after validating the model with the scenario, simulation of the research questions were done. In this research, the scenarios for eliminating the range of price fluctuations and elimination of the informed stakeholders and their effects on stock prices were reviewed.
According to the simulated scenarios of the Iranian stock market, due to its immature nature, eliminating controlling mechanisms such as the range of price fluctuations, in the short term the Market willbe highly instable, but in the long run the market tends to be more efficient.
Article Type:
Research/Original Article
Financial Research, Volume:20 Issue: 50, 2018
130 - 150  
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