Using a principal component analysis for multi-currencies-trading in the foreign exchange market

Hyun Woo Byun, Seungho Baek, Jae Joon Ahn, Kyong Joo Oh, Tae Yoon Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This study proposes a multi-currencies trading algorithm that applies a stock-trading algorithm to the foreign exchange (FX) market. Our algorithm applies a principal component analysis and artificial neural networks to produce an induced classifier from the FX market. Our algorithm yields reasonable profits. In addition, we discuss a basic procedure that the currency-trading algorithm must follow.

Original languageEnglish
Pages (from-to)683-697
Number of pages15
JournalIntelligent Data Analysis
Volume19
Issue number3
DOIs
Publication statusPublished - 2015 Jun 9

Fingerprint

Foreign Exchange Market
Currency
Principal component analysis
Principal Component Analysis
Artificial Neural Network
Profit
Profitability
Classifiers
Classifier
Financial markets
Neural networks

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Cite this

Byun, Hyun Woo ; Baek, Seungho ; Ahn, Jae Joon ; Oh, Kyong Joo ; Kim, Tae Yoon. / Using a principal component analysis for multi-currencies-trading in the foreign exchange market. In: Intelligent Data Analysis. 2015 ; Vol. 19, No. 3. pp. 683-697.
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Using a principal component analysis for multi-currencies-trading in the foreign exchange market. / Byun, Hyun Woo; Baek, Seungho; Ahn, Jae Joon; Oh, Kyong Joo; Kim, Tae Yoon.

In: Intelligent Data Analysis, Vol. 19, No. 3, 09.06.2015, p. 683-697.

Research output: Contribution to journalArticle

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