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)


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
Issue number3
Publication statusPublished - 2015 Jun 9


All Science Journal Classification (ASJC) codes

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

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