Agent-based computational economics: modeling economies as complex adaptive systems
Information Sciences—Informatics and Computer Science: An International Journal
Modeling chaotic behavior of stock indices using intelligent paradigms
Neural, Parallel & Scientific Computations - Special issue: Advances in intelligent systems and applications
Can Irrational Investors Survive? A Social-Computing Perspective
IEEE Intelligent Systems
Pattern-Oriented Agent-Based Modeling for Financial Market Simulation
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
A neural network with a case based dynamic window for stock trading prediction
Expert Systems with Applications: An International Journal
An agent-based approach to option pricing anomalies
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
An heterogeneous, endogenous and coevolutionary GP-based financial market
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Agent-based approach to option pricing anomalies
IEEE Transactions on Evolutionary Computation
The impact of information sharing mechanism to geographic market formation
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
GA-based solutions comparison for warehouse storage optimization
International Journal of Hybrid Intelligent Systems - Advances in Intelligent Agent Systems
Neuro-genetic system for stock index prediction
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
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This paper explores some of the empirical features generated in an agent-based computational stock market with market participants adapting and evolving over time. Investors view differing lengths of past information as being relevant to their investment decision-making process. The interaction of these memory lengths in determining market prices creates a kind of market ecology in which it is difficult for the more stable longer horizon agents to take over the market. What occurs is a dynamically changing market in which different types of agents arrive and depart depending on their current relative performance. This paper analyzes several key time series features of such a market. It is calibrated to the variability and growth of dividend payments in the United States. The market generates some features that are remarkably similar to those from actual data. These include magnifying the volatility from the dividend process, inducing persistence in volatility and volume, and generating fat-tailed return distributions