selection and reproduction in which the diversity of investment strategies is maintained through genetic programming. We find …

technique that analyses decision trees produced by Genetic Programming to discover classification rules. The aim of that work … investment. One of the main problems for any machine learning classifier is to deal with unbalanced classes. Specifically Genetic … Programming has limitation to deal with unbalanced environments. In a previous work we described the Repository Method, it is a …

selection and reproduction in which the diversity of investment strategies is maintained through genetic programming. We find …

symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available …

equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated …

capability of Genetic Programming (GP), and linked simulation-optimization for recreating the flux history of the unknown …

We present an agent-based simulation of an asset market with heterogeneously informed agents. Genetic programming is … systematic above-average returns. For all other agents, genetic programming finds a rich variety of trading strategies that are …

The purpose of this article is to present a novel genetic programming trading technique in the task of forecasting the … its effectiveness, we benchmark the forecasting performance of our genetic programming implementation with three … approach. The proposed genetic programming technique was found to demonstrate the highest trading performance in terms of …

increases the likelihood of systemic risk. We use a special form of the Strongly Typed Genetic Programming (STGP) technique to …

approach combines a genetic programming (GP) algorithm that evolves a composite rule from basic job attributes with an …