[3] Agent-based models based on heterogeneous and boundedly rational (learning) agents have shown to be able to explain the empirical features of financial markets better than traditional financial models that are based on representative rational agents.

[4] The software creates an agent-based model for a particular stock, consisting of a population of trader agents and a virtual market.

This intends to increase the robustness of the model and its ability to adapt to changing market circumstances.

[8] In a study of profitability of technical trading in the foreign exchange markets, researchers using Adaptive Modeler found economically and statistically significant out-of-sample excess returns (after transaction costs) for the six most traded currency pairs.

[9] Adaptive Modeler was also used to study the impact of different levels of trader rationality on market properties and efficiency.

[10] It was found that artificial markets with more intelligent traders (compared to markets with less intelligent or zero-intelligence traders) showed improved forecasting performance, though also experienced higher volatility and lower trading volume (consistent with earlier findings).