An investigation into the recurring patterns of forex time series data
Countless theories have been developed by both researchers and financial analyst in an attempt to explain the fluctuation of forex price. By obtaining an intimate understanding of the forex market, traders will hopefully be able to forecast and react to forex price oscillations on-the-fly towards...
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my.sunway.eprints.3182019-04-26T07:45:00Z http://eprints.sunway.edu.my/318/ An investigation into the recurring patterns of forex time series data Yong, Yoke Leng * Lee, Yunli * Ngo, David Chek Ling * QA Mathematics Countless theories have been developed by both researchers and financial analyst in an attempt to explain the fluctuation of forex price. By obtaining an intimate understanding of the forex market, traders will hopefully be able to forecast and react to forex price oscillations on-the-fly towards making a profitable investment. In this paper, an investigation into the underlying theory that there exists repeating patterns within the time series data which forms the basis of technical analysis is conducted. The assumption that certain patterns do develop over time and the forex market does not fluctuate in a random manner is used to establish the fact that history repeats itself in forex trading. The patterns and repetitions unveiled within the forex historical data would be an important element for forex forecasting. Springer 2015 Book Section PeerReviewed text en http://eprints.sunway.edu.my/318/1/An%20Investigation%20Into%20the%20Recurring%20Patterns%20of%20Forex%20Time%20Series%20Data.pdf Yong, Yoke Leng * and Lee, Yunli * and Ngo, David Chek Ling * (2015) An investigation into the recurring patterns of forex time series data. In: Advances in Swarm and Computational Intelligence 6th International Conference, ICSI 2015 held in conjunction with the Second BRICS Congress, CCI 2015, Beijing, China, June 25-28, 2015, Proceedings Part III. Lecture Notes in Computer Science (9142). Springer, pp. 87-97. ISBN 978-3-319-20468-0 http://link.springer.com/book/10.1007/978-3-319-20469-7 Doi:10.1007/978-3-319-20469-7_11 |
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QA Mathematics Yong, Yoke Leng * Lee, Yunli * Ngo, David Chek Ling * An investigation into the recurring patterns of forex time series data |
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Countless theories have been developed by both
researchers and financial analyst in an attempt to explain the fluctuation of forex price. By obtaining an intimate
understanding of the forex market, traders will hopefully be able to forecast and react to forex price oscillations on-the-fly towards making a profitable investment. In this paper, an investigation into the underlying theory that there exists repeating patterns within the time series data which forms the basis of technical analysis is conducted. The assumption that certain patterns do develop over time and the forex market does not fluctuate in a random manner is used to establish the fact that history repeats
itself in forex trading. The patterns and repetitions unveiled within the forex historical data would be an important element for forex forecasting. |
format |
Book Section |
author |
Yong, Yoke Leng * Lee, Yunli * Ngo, David Chek Ling * |
author_facet |
Yong, Yoke Leng * Lee, Yunli * Ngo, David Chek Ling * |
author_sort |
Yong, Yoke Leng * |
title |
An investigation into the recurring patterns of forex
time series data |
title_short |
An investigation into the recurring patterns of forex
time series data |
title_full |
An investigation into the recurring patterns of forex
time series data |
title_fullStr |
An investigation into the recurring patterns of forex
time series data |
title_full_unstemmed |
An investigation into the recurring patterns of forex
time series data |
title_sort |
investigation into the recurring patterns of forex
time series data |
publisher |
Springer |
publishDate |
2015 |
url |
http://eprints.sunway.edu.my/318/1/An%20Investigation%20Into%20the%20Recurring%20Patterns%20of%20Forex%20Time%20Series%20Data.pdf http://eprints.sunway.edu.my/318/ http://link.springer.com/book/10.1007/978-3-319-20469-7 |
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1644324298130718720 |