Macro-Economic Time-Series Forecasting Using Linear Genetic Programming
Roberto Sanchez1, Javier Martinez, Benjamin Baran
1Universidad Católica “Ntra. Sra. de la Asunción”
Available Online December 2008.
- 10.2991/jcis.2008.115How to use a DOI?
- Genetic Programming, Forecasting, Macro-Economic, Time Series
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.
- © 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/).
Cite this article
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 -