Rule selection, fuzzy logic and time series

Author

Benachenhou, Dalila

Author_Institution

Dept. of Math. & Stat., American Univ., Washington, DC, USA

fYear

1994

fDate

18-21 Dec 1994

Firstpage

189

Lastpage

193

Abstract

It is difficult to extract trading rules for financial trading systems. One reason is that the data often leads to conflicting rules, i.e., rules that have the same left-hand side but different right hand side. In this paper, we explore ways to deal with the problem of inconsistent rules using US ten-years bond time series data. We explore Wang´s method, and identify a particular shortcoming. In addition, we explore the use of frequency, and the last-in-sequence methods in choosing among inconsistent rules. We conclude that frequency can be used to develop short-term systems, while last-in-sequence produces overly biased rules

Keywords

data analysis; financial data processing; fuzzy logic; knowledge based systems; time series; uncertainty handling; US ten-years bond time series data; financial trading systems; fuzzy logic; inconsistent rules; last-in-sequence methods; rule selection; Automatic control; Clustering algorithms; Control systems; Data mining; Frequency; Fuzzy logic; Fuzzy systems; Inference algorithms; Input variables; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-2125-1

Type

conf

DOI

10.1109/IJCF.1994.375101

Filename

375101