Under adaptive learning, recursive algorithms are proposed to represent how agents update their beliefs over time. For applied purposes these algorithms require initial estimates of agents perceived law of motion. Obtaining appropriate initial estimates can become prohibitive within the usual...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

We discuss the problems of strategy selection in the framework of mathematical finance, stochastic control, and risk management in finance and economics. A problem setting that takes in to account a possibility of short term forecasting for market parameters is suggested. In this setting,...