Chapter 6 An Evolutionary Adaptive Learning
Model with Fundamentalists and
Moving Average Traders
6.1 Introduction
Chapters 2 through 5 of this thesis contain empirical analyses whether technical trading has statistically significant forecasting power and yields economically significant profits when applied to financial time series. The present chapter builds a simple theoretical financial market model with fundamentalists and technical analysts.An important question in heterogeneous agents modeling is whether irrational traders can survive in the market, or whether they would lose money and are driven out of the market by rational investors, who would trade against them and drive prices back to fundamentals, as argued by e.g. Friedman (1953). In the last decade a number of theoretical and/or computational heterogeneous agent models, with fundamentalist traders competing against technical analysts, have been developed, see e.g. in Frankel and Froot (1988), De Long et al. (1989, 1990), Kirman (1991), Wang (1994), Lux (1995), Arthur et al. (1997), Brock and Hommes (1997, 1998), Farmer (1998), Hong and Stein (1999) and LeBaron et al. (1999). A common feature of these contributions is that technical traders may at times earn positive profits, survive evolutionary competition and need not be driven out of the market by trading strategies based upon economic fundamentals.
Brock and Hommes (1998) investigate the dynamical behavior of a simple financial market model with heterogeneous adaptively learning traders, where the fraction of traders following a certain forecasting rule changes over time. The traders are restricted