Horizontal generalization properties of fuzzy rule-based trading models

被引：0
|
作者：
Pereira, Celia da Costa [1 ]
Tettamanzi, Andrea G. B. [1 ]
机构：
[1] Univ Milan, Dipartimento Tecnol Informazione, I-26013 Crema, Italy
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2008年 / 4974卷
关键词：
data mining; modeling; trading; evolutionary algorithms;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We investigate the generalization properties of a data-mining approach to single-position day trading which uses an evolutionary algorithm to construct fuzzy predictive models of financial instruments. The models, expressed as fuzzy rule bases, take a number of popular technical indicators on day t as inputs and produce a trading signal for day t + 1 based on a dataset of past observations of which actions would have been most profitable. The approach has been applied to trading several financial instruments (large-cap stocks and indices), in order to study the horizontal, i.e., cross-market, generalization capabilities of the models.
引用
收藏
页码：93 / 102
页数：10
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