CAMREC: 3 New CPM reports

From: the Campaign for Real Economics (camrec@mmu.ac.uk)
Date: Tue Mar 06 2001 - 12:26:06 GMT

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    From: the Campaign for Real Economics <camrec@mmu.ac.uk>
    Date: Tue, 06 Mar 2001 12:26:06 +0000
    Subject: CAMREC: 3 New CPM reports
    

         Competition in Intermediated
       Markets: Statistical signatures
            and critical densities

    CPM Report No.: 01-79
    Date: 1st March 2001

    Abstract

    In conventional economic theory, competition is an unmodelled
    process that is claimed to drive all economic actors to behave as
    if they were constrained optimisers. What is actually modelled in
    conventional economic theory is either a competitive equilibrium
    that is said to capture the result of the unmodelled competitive
    process or a game between two or, occasionally, among three
    agents. The common element in these approaches is the absence
    of any consideration of the effect of interaction among more than
    three economic actors at any one time. This is despite the natural
    presumption that such interaction is essential to any process of
    competition.

    The purpose of this paper is to demonstrate that the interaction
    excluded from conventional economic theory gives rise to the
    distributions of data observed in real markets. The well known
    “fat-tailed” (leptokurtic) distributions found in high frequency
    time series data for financial markets is shown to characterise
    high frequency retail market data as well. This and other
    statistical signatures of real markets are replicated in an abstract
    simulation model of markets in which intermediaries (brokers or
    jobbers) can function. It is shown that a high density of agents
    in the social network is necessary for intermediation to be viable
    and for the preponderance of demands to be satisfied.
    Moreover, the leptokurtic statistical signature characterises only
    markets satisfying that density condition.

    social simulation, statistical signatures, self organised criticality

    Available at:
            http://www.cpm.mmu.ac.uk/cpmrep79.html

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         Game Theory: Limitations and
                an Alternative

    CPM Report No.: 01-80
    Date: 5th March 2001

    Abstract

    The purpose of this paper is to describe current practice in the
    game theory literature, to identify particular characteristics that
    ensure the literature is remote from anything we observe and to
    demonstrate an alternative drawn from agent based social
    simulation. The key issue is the process of social interaction
    among agents. A survey of game theoretic models found no
    models representing interaction among more than three agents,
    though sometimes more agents were involved in a round robin
    tournament. An ABSS model is reported in which there is a
    dense pattern of interaction among agents and outputs from the
    model are shown to have the same statistical signature as
    high-frequency data from competitive retail and financial
    markets. Moreover, the density of agent interaction is seen to be
    necessary both to obtain the validating statistical signature and
    for simulated market efficiency. As far as competitive markets
    are concerned, game theoretic models evidently assume away the
    source of the properties observed in real high frequency data and
    also the properties required for market efficiency.

    markets, density, interaction, statistical signature

    Available at:
            http://www.cpm.mmu.ac.uk/cpmrep80.html

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              The Importance of
            Representing Cognitive
           Processes in Multi-Agent
                     Models

    CPM Report No.: 01-81
    Date: 5th March 2001

    Abstract

    We distinguish between two main types of model: predictive and
    explanatory. It is argued (in the absence of models that predict on
    unseen data) that in order for a model to increase our
    understanding of the target system the model must credibly
    represent the structure of that system, including the relevant
    aspects of agent cognition. Merely “plugging in” an existing
    algorithm for the agent cognition will not help in such
    understanding. In order to demonstrate that the cognitive model
    matters, we compare two multi-agent stock market models that
    differ only in the type of algorithm used by the agents to learn.
    We also present a positive example where a neural net is used to
    model an aspect of agent behaviour in a more descriptive
    manner.

    net, genetic programming, representation, prediction,
    explanation, cognition, stock market, negotiation.

    Available at:
            http://www.cpm.mmu.ac.uk/cpmrep81.html

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