Macro-Economic Time-Series Forecasting Using Linear Genetic Programming

DOI

10.2991/jcis.2008.115How to use a DOI?

Keywords

Genetic Programming, Forecasting, Macro-Economic, Time Series

Abstract

Recent studies in financial economics suggest that good technical analysis may have a merit in data series prediction. Linear Genetic Programming (LGP) is a genetic programming variant that evolves sequences of instructions from an imperative programming language. This paper presents a LGP approach to search times series forecasting rules. Results for three Paraguayan macro-economic time series (Consumer Price Index, Gross Internal Product & Paraguayan import from Argentina) and one artificial time series indicate that these prediction rules may be more accurate to forecast future values than some standard statistical models in use.

Copyright

© 2008, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Roberto Sanchez
AU  - Javier Martinez
AU  - Benjamin Baran
PY  - 2008/12
DA  - 2008/12
TI  - Macro-Economic Time-Series Forecasting Using Linear Genetic Programming
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 684
EP  - 689
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.115
DO  - 10.2991/jcis.2008.115
ID  - Sanchez2008/12
ER  -