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

doi:10.3233/IDA-150738

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

Department of Industrial Engineering

Research output: Contribution to journal › Article › peer-review

3 Citations (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 language	English
Pages (from-to)	683-697
Number of pages	15
Journal	Intelligent Data Analysis
Volume	19
Issue number	3
DOIs	https://doi.org/10.3233/IDA-150738
Publication status	Published - 2015 Jun 9

Bibliographical note

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© 2015 - IOS Press and the authors. All rights reserved.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.3233/IDA-150738

Cite this

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AB - 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.

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

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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