The creative destruction wrought by high-frequency algorithmic tradinghas raised increasing concerns about the eect of machine learning behaviorsand ultra high-frequency trading in finnancial markets. By employing a geneticalgorithm with a classifer system as an adaptive learning tool, we...

How do traders process and learn from market information, what trading strategies should they use, and how does learning affect the market? This paper proposes a two-sided learning model of an artificial limit order market with asymmetric information to address these issues. Using a genetic...

By incorporating behavioral sentiment to a model of limit order market, we show that behavioral sentiment not only helps to replicate most of the stylized facts simultaneously in limit order markets, but also plays a unique role in explaining these stylized facts that cannot be explained by...

We examine the effect of learning of uninformed traders in a dynamic limit order market with asymmetric and short-lived information. We show that the learning is effective and valuable with respect to information acquisition, forecasting and buy-sell decision accuracies, and profit opportunity...