Access Restriction

Author Parque, V. ♦ Mabu, S. ♦ Hirasawa, K.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Training ♦ Biological system modeling ♦ Economic indicators ♦ Robustness ♦ Testing ♦ Genetics ♦ Measurement
Abstract Financial innovation is continuously testing the asset selection models, which are the key both for building robust portfolios and for managing diversified risk. This paper describes a novel evolutionary based scheme for the asset selection using Robust Genetic Network Programming(r-GNP). The distinctive feature of r-GNP lies in its generalization ability when building the optimal asset selection model, in which several training environments are used throughout the evolutionary approach to avoid the over-fitting problem to the training data. Simulation using stocks, bonds and currencies in developed financial markets show competitive advantages over conventional asset selection schemes.
Description Author affiliation: Graduate School of Information, Production and Systems, Waseda University, Japan (Parque, V.; Mabu, S.; Hirasawa, K.)
ISBN 9781424468898
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-11-21
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424468904
Size (in Bytes) 499.96 kB
Page Count 6
Starting Page 1021
Ending Page 1026

Source: IEEE Xplore Digital Library