Agent-Based Computational Economics: Overview and Brief History

Scientists seek to understand how real-world systems work. Models devised for scientific purposes must always simplify reality. However, scientists should be permitted to tailor these simplifications to purposes at hand; they should not be forced to distort reality in specific predetermined ways in order to apply a modeling approach. Adherence to this modeling precept was a key goal motivating my development of Agent-Based Computational Economics (ACE), a variant of agent-based modeling characterized by seven specific modeling principles. This perspective provides an overview of ACE and a brief history of its development

Pretests for genetic-programming evolved trading programs: “zero-intelligence” strategies and lottery trading

The original publication is available at www.springerlink.com ; ISBN 978-3-540-46484-6 ; ISSN 0302-9743 (Print) 1611-3349 (Online)International audienceOver the last decade, numerous papers have investigated the use of GP for creating financial trading strategies. Typically in the literature results are inconclusive but the investigators always suggest the possibility of further improvements, leaving the conclusion regarding the effectiveness of GP undecided. In this paper, we discuss a series of pretests, based on several variants of random search, aiming at giving more clearcut answers on whether a GP scheme, or any other machine-learning technique, can be effective with the training data at hand. The analysis is illustrated with GP-evolved strategies for three stock exchanges exhibiting different trends

Information aggregation and computational intelligence

This study examines the possibility that the computational intelligence (CI) inspired tools can effectively aggregate the rich information generated from the Web 2.0 economy and, thereby, enhance the quality of decision-making. Despite many advancements and commendable applications of CI in recent years, this issue has not been well addressed. We argue that this question is intimately related to the central issue of the socialist calculation debate since the time of Friedrich Hayek. In terms of information aggregation, we examine whether there is a better engineering than the market mechanism. More precisely, we focus on whether the CI-driven sentiment analysis can generate signals like prices and whether CI can process unstructured text data better than the market. We argue that Web 2.0 economy may not be able to set us free from information overload problems that have long coexisted with the presence of markets. We attribute this to the tacitness and subjectivity of knowledge and the recursive (feedback) characteristic of the sentiments. In this sense, Hayek’s fundamental assertion that the effectiveness of the market mechanism may not be so much conditioned on the information and communication technology still applies

Agent-Based Computational Economics: Overview and Brief History

Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific modeling principles. This perspective provides an overview of ACE, a brief history of its development, and its role within a broader spectrum of experiment-based modeling methods

CES-509 Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework

This paper extends a previous model where we examined the markets' microstructure dynamics by using Genetic Programming as a trading rule inference engine, and Self Organizing Maps as a cluster- ing machine for those rules. However, an assumption we made in that model was that clusters, and thus trading strategy types, had to remain the same over time. This assumption could be considered unrealistic, but it was necessary for the purposes of our tests. For this reason, in this paper we extend this model by relaxing this assumption. Hence our framework does not lie on pre-speci?ed types, nor do these types remain the same throughout time. This allows us to investigate the dynamics of market behavior and more speci?cally whether successful strategies from the past can be successfully applied to the future. In the past, we investigated this phenomenon by using a simple ?tness test. Neverthe- less, a drawback of that approach was that because of its simplicity, it could only o?er limited understanding of the complex dynamics of mar- ket behavior. With the extended model we can thus have a more realistic view of the markets and hence draw safer conclusions about their behav- ior. Empirical results show that market behavior is non-stationary, and thus agents' strategies need to continuously co-evolve with the market, in order to remain eff?ective

Agent-Based Modeling of the El Farol Bar Problem

In this paper, we study the self-coordination problem as demonstrated by the well-known El Farol problem (Arthur, 1994), which has later become what is known as the minority game in the econophysics community. While the El Farol problem or the minority game has been studied for almost two decades, existing studies are mostly only concerned with efficiency. The equality issue, however, has been largely neglected. In this paper, we build an agent-based model to study both efficiency and equality and ask whether a decentralized society can ever possibly self-coordinate a result with the highest efficiency while also maintaining the highest degree of equality. Our agent-based model shows the possibility of achieving this social optimum. The two key determinants to make this happen are social preferences and social networks. Hence, not only doe institutions (networks) matter, but individual characteristics (preferences) also matter. The latter are open to human-subject experiments for further examination.El Farol Bar problem, Social Preferences, Social Networks, Self-Organization, Emergence of Coordination.

How Far Can We Go Through Social System?

The paper elaborates an endeavor on applying the algorithmic information-theoretic computational complexity to meta-social-sciences. It is motivated by the effort on seeking the impact of the well-known incompleteness theorem to the scientific methodology approaching social phenomena. The paper uses the binary string as the model of social phenomena to gain understanding on some problems faced in the philosophy of social sciences or some traps in sociological theories. The paper ends on showing the great opportunity in recent social researches and some boundaries that limit them