Cesáreo Hernández

Strategic Behaviour in Continuous Double Auction

We analyze with a bottom-up approach the competition between artificial intelligent agents in Continuous Double Auction markets in terms of allocative efficiency, price convergence and emergence or not of Nash equilibriums. In previous works agents have a fixed bidding strategy during the auction, usually under symmetric environments. In our simulations we allow the soft-agents to learn not only about how much they should bid or offer, but also about possible switching between the alternative strategies. We examine the behaviour of strategic traders under general supply and demand schedules (asymmetric environments) thus extending previous results.

Market Failure Caused by Quality Uncertainty

The classical argument used to explain why markets can fail when there is product quality variability (e.g. the used car market) relies heavily on the presence of asymmetric information —i.e. there must exist some reliable quality indicators that can be observed by sellers, but not by buyers. Using computer simulation, this paper illustrates how such market failures can occur even in the absence of asymmetric information. The mere assumption that buyers estimate the quality of the product they buy using their past experience in previous purchases is enough to observe prices drop, market efficiency losses, and systematic underestimation of actual product quality. This alternative explanation is shown to be valid for a very wide range of learning rules and in various market contexts.

An Artificial Economics View of the Walrasian and Marshallian Stability

The experiments discussed below are an attempt to examine two concepts of instability which stem from two different models of market adjustment used in Economics: Walrasian (W) and Marshallian (M) instability. The M model views volume as adjusting in response to the difference between demand price and supply price at that volume. The W model views price as changing in response to excess demand at that price. Do the M and the W models have a firm foundation on micro-motives, or are they just macro abstractions that we could dispense of in Microeconomics?

Learning in Continuous Double Auction Market

We start from the fact, that individual behaviour is always mediated by social relations. A heuristic is not good or bad, rational or irrational, but only relative to an institutional environment. Thus for a given environment, the Continuous Double Action (CDA) market, we examine the performance of alternative intelligent agents, in terms of market efficiency and individual surplus.

The Effect of Transaction Costs on Artificial Continuous Double Auction Markets

Fast price convergence and high allocative market efficiency (close to 100%) are two of the most robust results in Experimental Economics. When human-subjects are replaced by artificial-agents, high allocative market efficiency is also attained even if the artificial agents have zero intelligence, but price convergence depends on the agents’ learning. In this paper we study the sensitivity of Continuous Double Auction performance to the imposition of monetary costs in the market. We find that transactions costs reduce market efficiency. Price convergence results are very different when the monetary cost is imposed on the transaction or on the submissions to buy or to sell. Our agent-based market model confirms and extends previous Experimental Economics market results, and provides new behavioral explanations of the price dynamics.

The Application of the Viable System Model to Enhance Organizational Resilience

The interest in how to build resilient organizations is increasing in the last two decades. However , there is no formal and accepted framework yet. In this paper, we argue that the application of the principles of the Viable System Model (VSM) improves organizational resilience. We also argue that the VSM constitutes a valid framework to design resilient organizations.

New Insights on the Emergence of Classes Model

We show the results of a detailed replication of the Emergence of Classes Model Axtell et al. (2004). We study the effect of possible biases on the original proposal and we find additional results and conclusions. We also explore the effects of minor changes on the decision rules that agents play.

Sixty Years of Economics: Some Lessons for the Future

Economics is contextual and evolves. For this reason, in this chapter, I have selected some relevant milestones of a long period of 60 years. The choice, the questions and the conclusions are personal and probably controversial. The chapter begins with the great failure of the Economy: the gap in the distribution of wealth even in developed countries. It continues asking the following questions: What have we learned from the seventies crisis? What are we learning from the current crisis? What is wrong with Economics as a social science? Can Experimental Economics allow us to understand and accommodate the social complexity of the Economy? What is the scope of Artificial Economics? Finally, since Artificial Economics provides solutions to complex problems, can we export socially inspired methods to other areas of Management Engineering? I conclude that there are tools to improve Economics and to help us in designing proper institutional frameworks. However, solving the actual economic challenges will require changes in methods and institutions far beyond Economic Policy. The changes must be institutional and can not be delayed. Not so much improvements in Economic Policy as changes in Political Economy.

Agent-Based Experimental Economics in Signaling Games

In this paper we built up an agent-based model inspired by human-subject behaviour in a signaling game experiment. The behavioural patterns of players observed in the experiment are classified in terms of attitudes, emotions and frugal and fast heuristics. We build up an agent-based model where artificial agents are endowed with these cognitive patterns by means of an endorsement scheme. We show the relationship between cognition and Multi-Agent interaction. We validate the model since it reproduces well the behavioural patterns observed in the human-subjects experiment.