dc.contributor.author | Fieldsend, Jonathan E. | |
dc.contributor.author | Singh, Sameer | |
dc.date.accessioned | 2013-07-10T13:04:47Z | |
dc.date.issued | 2002-08-07 | |
dc.description.abstract | Recent studies confront the problem of multiple error terms through summation. However this implicitly assumes prior knowledge of the problem's error surface. This study constructs a population of Pareto optimal Neural Network regression models to describe a market generation process in relation to the forecasting of its risk and return. | en_GB |
dc.identifier.citation | 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, Hawaii, 12-17 May 2002, pp. 388 - 393 | en_GB |
dc.identifier.doi | 10.1109/IJCNN.2002.1005503 | |
dc.identifier.uri | http://hdl.handle.net/10871/11685 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.subject | Neural networks | en_GB |
dc.subject | optimization | en_GB |
dc.subject | Prediction | en_GB |
dc.subject | financial data processing | en_GB |
dc.subject | forecasting theory | en_GB |
dc.subject | neural nets | en_GB |
dc.subject | optimisation | en_GB |
dc.subject | risk management | en_GB |
dc.subject | stock markets | en_GB |
dc.subject | time series | en_GB |
dc.subject | Casting | en_GB |
dc.subject | Computer errors | en_GB |
dc.subject | Econometrics | en_GB |
dc.subject | Economic forecasting | en_GB |
dc.subject | Euclidean distance | en_GB |
dc.subject | Input variables | en_GB |
dc.subject | Predictive models | en_GB |
dc.subject | Smoothing methods | en_GB |
dc.title | Pareto multi-objective non-linear regression modelling to aid CAPM analogous forecasting | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2013-07-10T13:04:47Z | |
dc.identifier.isbn | 0780372786 | |
dc.identifier.issn | 1098-7576 | |
dc.description | Copyright © 2002 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | en_GB |