درخت حوزه‌های تخصصی

Although theoretical and empirical literature regarding the stylized facts shows evidence of their correlations to herding behavior in financial markets, the causes of such phenomena are still unknown. Using an agent-based model strengthened by the competition co-evolution algorithm (STGP) technique, this study provides laboratory evidence on capital market dynamics and analyses the behavioral foundations of stylized facts such as fat tails, leverage effects, and volatility clustering. The simulated stock markets consist of two groups; the “Best agents”, which are a small portion of artificial agents, and the “Residual agents”, which are the main group of artificial agents. The best performance in terms of breeding fitness returns is the main feature of the “Best agents”. More, the size of the “Best Agents” group is specified as 2.5%, 5%, 10% &20% of the total population size. An agent-based model consists of two portions, a two thousand population of trader agents that each has its decision-making strategy, and a virtual market that creates the trading strategies. Then the model evolved step by step using a feed with real quotes of the financial instruments by Adaptive Modeler. A training period is considered 2500 bars (started in November 2003), and the test period started in December 2013. The observation shows that the herding behavior in the price series created by the “Residual agents” is less than the “Best agents” series. Therefore, the greater diversity of trade strategies as the genetic differences of artificial agents leads to less herding. The observations exhibit that the volatility clustering, leverage effects, and nonlinear dependence are more likely to experience in the price series generated by “Best gents”. Furthermore, observations indicate that if the population is well diversified in terms of trading strategies, the efficiency of the market increases.

The causality between tourism growth and economic growth would not be very accurate regardless of the environmental factors affecting them such as the oil revenues. The present study investigates the effects of oil revenues on the causality between them, to present the difference between the two variables in oil-exporting countries. We examined the causal relationship using Dumitrescu and Hurlin’s model (2012) and the trivariate method in 9 oil-exporting countries from 1996 to 2019. The results show a one-way causal relationship between economic growth and tourism promotion in two variate causality but no relationship was found between them in trivariate. However, one-way causality is weakened when oil revenues are introduced. The causality of economic growth is not confirmed in the presence of oil revenues, as the causal relationship in the two-variable test is affected by the abundance of oil revenues. JEL Classification: F49, L83, O47, C21, C23