Artificial Financial Markets: An Agent Based Approach to Reproduce Stylized Facts and to study the Red Queen Effect

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{Martinez-Jaramillo:thesis,
  author =       "Serafin Martinez-Jaramillo",
  title =        "Artificial Financial Markets: An Agent Based Approach
                 to Reproduce Stylized Facts and to study the Red Queen
                 Effect",
  school =       "Centre for Computational Finance and Economic Agents,
                 University of Essex",
  year =         "2007",
  address =      "UK",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://cswww.essex.ac.uk/Research/CSP/finance/papers/Martinez-PhD2007.pdf",
  size =         "198 pages",
  abstract =     "Stock markets are very important in modern societies
                 and their behaviour have serious implications in a wide
                 spectrum of the world's population. Investors,
                 governing bodies and the society as a whole could
                 benefit from better understanding of the behaviour of
                 stock markets. The traditional approach to analyze such
                 systems is the use of analytical models. However, the
                 complexity of financial markets represents a big
                 challenge to the analytical approach. Most analytical
                 models make simplifying assumptions, such as perfect
                 rationality and homogeneous investors, which threaten
                 the validity of analytical results. This motivates the
                 use of alternative methods. For those reasons, the
                 study of such markets is a fertile field to use the
                 agent-based methodology.

                 In this work, we developed an artificial financial
                 market and used it to study the behaviour of stock
                 markets. In this market, we model technical,
                 fundamental and noise traders. The technical traders
                 are non-simple genetic programming based agents that
                 co-evolve (by means of their fitness function) by
                 predicting investment opportunities in the market using
                 technical analysis as the main tool. Such traders are
                 equipped with an investment strategy that we consider
                 to be realistic and we avoid any kind of strong
                 assumptions about the agents' rationality, utility
                 function or risk aversion.!

                 Changes in some parameters and in the agents behaviour
                 produce different properties of the stock price series
                 that we analyze. In this paper we investigate the
                 different conditions under which the statistical
                 properties of an artificial stock market resemble those
                 of the real financial markets. Additionally, we modeled
                 the pressure to beat the market by a behavioural
                 constraint imposed on the agents related to the Red
                 Queen principle in evolution. The Red Queen principle
                 is a metaphor of a co-evolutionary arms race between
                 species. We investigate the effect of such constraint
                 on the price dynamics and the wealth distribution of
                 the agents after several periods of trading in the
                 different simulation cases. We have demonstrated how
                 evolutionary computation plays a key role in studying
                 stock markets.",
}

Genetic Programming entries for Serafin Martinez Jaramillo

Citations