TABLE 3.

Financial markets

Name/focus	Description	Results/findings	References
Santa Fe artificial stock market	An artificial stock market in which independent adaptive agents can purchase and sell stock.	The market behavior is an emergent outcome of the agent's behavior, and it can include bubbles and crashes.	(Palmer et al., 1994)
Trade Network Game (TNG) Laboratory	A computational model for studying the emergence of trade networks among sellers, dealers, and buyers.	Agents look for trade partners, participate in risky trades, which are modeled as noncooperative games, and evolve their strategies over time.	(McFadzean et al., 2001)
Foreign exchange	An artificial model of a foreign exchange market is developed using a genetic algorithm, with agents having internal representations of market situations.	A quantitative explanation of micro–macro relations in markets corroborated with real‐world data. Emergent effects were explained by a “phase transition of forecast variety,” caused by the interaction of demand–supply and agent forecasts.	(Izumi & Ueda, 2001)
Macrofinance	An agent‐based simulation of the stock market where participants adapt and evolve as the simulation runs.	Agents coevolve their trading rules based on different levels of past data while trying to optimize their wealth.	(LeBaron, 2001)
Investment trading	An artificial financial market was developed to study stock markets. The model consists of three types of traders: noise traders, fundamental traders, and technical traders, each with a different trading strategy.	The work showed that evolutionary computation can be used to study stock markets and identified which conditions were necessary to produce realistic behaviors.	(Martinez‐Jaramillo & Tsang, 2009)
Bounded rationality of trading	An artificial market model with selection pressures to study whether bounded rationality observed in trade behaviors could have an evolutionary basis.	A decision‐making model with bounded rationality has the capacity to become a stable evolutionary strategy and entities with bounded rationality can survive in a competitive market.	(Kinoshita et al., 2013)