ABSTRACT
The HSM also matches aggregate price behavior in both the negative and the positive feedback experiments very well. The time series of the fractions of the different forecasting heuristics provide an intuitive explanation of how individual learning leads to different aggregate price behavior. In the negative feedback treatment, the ADA strategy performs the best and within 20 periods it captures more than 90% of the market, thus enforcing convergence towards the RE fundamental equilibrium price. In contrast, in the positive feedback treatment, the strong and weak trend-following rules dominate the market, amplifying price fluctuations. The difference in aggregate behavior is thus explained by the fact that trend-following rules are successful in a positive feedback environment reinforcing price oscillations and persistent deviations from the fundamental equilibrium benchmark price, while the trend-following rules are driven out by ADA in the case of negative feedback. Self-confirming coordination on trend-following rules in a positive expectations feedback environment has an aggregate effect with realized market prices deviating significantly and persistently from the RE benchmark.
