We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We analyze the learning process of purely and impurely altruistic...

This chapter surveys research on agent-based models used in finance. It will concentrate on models where the use of computational tools is critical for the process of crafting models which give insights into the importance and dynamics of investor heterogeneity in many financial settings.

This paper examines the learning dynamics of boundedly rational agents, who are asked to voluntarily contribute to a discrete public good. In an incomplete information setting, we discuss contribution games and subscription games, the latter including a money-back guarantee in case of provision...

Dieser Beitrag gibt einen Überblick über Ansatzpunkte und Möglichkeiten zur Integration von Lernprozessen in volkswirtschaftliche Fragestellungen. Es werden alternative Methoden vorgestellt, individuelle aber auch gesellschaftliche Lernenvorgänge in ökonomischen Modellen zu erfassen.

The standard approach to modelling consumption/saving problems is to assume that the decisionmaker is solving a dynamic stochastic optimization problem However under realistic descriptions of utility and uncertainty the optimal consumption/saving decision is so difficult that only recently...

In recent years, the learnability of rational expectations equilibria (REE) and determinacy of economic structures have rightfully joined the usual performance criteria among the sought-after goals of policy design. Some contributions to the literature, including Bullard and Mitra (2001) and...

Various approaches used in Agent-based Computational Economics (ACE) to model endogenously determined interactions between agents are discussed. This concerns models in which agents not only (learn how to) play some (market or other) game, but also (learn to) decide with whom to do that (or not).