Agents, initially endowed with a certain sum of money, must decide in each time period of the simulation how to allocate their capital between the two assets. If the market state in a given period matches the descriptor of a forecasting rule, the rule is said to be activated. A number of an agent's forecasting rules may be activated at a given time, thus giving the agent many possible forecasts from which to choose. An agent decides which of the active forecasts to use by choosing at random among the active forecasts with a probability proportional to its accuracy, a measure that indicates how well the rule has performed in the past. Once the agent has chosen a specific rule to use, the rule is employed to make an investment decision.
Agents determine how much stock to buy, sell or hold, using a standard risk-aversion calculation.
They submit their decisions to the market specialist, an extra agent in the market who functions as a market-maker. Whenever the GA is invoked, it substitutes new forecasting rules for a fraction of the least-fit forecasting rules in each agent's pool of rules. New rules are created by first applying the genetic operators of mutation and crossover to the bit strings of the more successful rules in the agent's rule pool. The GA may be compared to a real-world consultant. It replaces current poorly performing rules with rules that are likely to perform better, much the same way as a consultant urges her client to replace poorly performing trading strategies with those that are likely to be more profitable.