- 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.",
-
notes = "Supervisor: Edward P. K. Tsang
Co-supervisor: Sheri Markose",
