Application of Support Vector Machine on Algorithmic Trading
I tiakina i:
| I whakaputaina i: | Proceedings on the International Conference on Artificial Intelligence (ICAI) (2018), p. 400 |
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| Kaituhi matua: | |
| Ētahi atu kaituhi: | , , , |
| I whakaputaina: |
The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)
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| Ngā marau: | |
| Urunga tuihono: | Citation/Abstract Full Text Full Text - PDF |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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MARC
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| 001 | 2136876869 | ||
| 003 | UK-CbPIL | ||
| 035 | |a 2136876869 | ||
| 045 | 2 | |b d20180101 |b d20181231 | |
| 084 | |a 184240 |2 nlm | ||
| 100 | 1 | |a Szklarz, J |u Programmer, Izertis S.L, Gijón, Asturias, Spain | |
| 245 | 1 | |a Application of Support Vector Machine on Algorithmic Trading | |
| 260 | |b The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp) |c 2018 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a The following research provides a thoughtful analysis regarding the use of machine learning techniques applied to algorithmic trading using common indexes such as the S&P500 and the Chicago Board Options Exchange Market Volatility Index (VIX). A trading simulation is carried out in order to test the efficiency of the algorithms in up trending and down trending periods. Statistical and economic performance measures are obtained and compared in order to discuss the most effective technique. The inputs used in the analysis are well-known quantitative indicators such as the Relative Strength Index and the Moving Average Convergence-Divergence. The relevance of the results lies in the use of separated training models for each kind of trend. | |
| 653 | |a Algorithms | ||
| 653 | |a Divergence | ||
| 653 | |a Machine learning | ||
| 653 | |a Performance indices | ||
| 653 | |a Trends | ||
| 653 | |a Support vector machines | ||
| 653 | |a Decision making | ||
| 653 | |a Volatility | ||
| 653 | |a Computer simulation | ||
| 653 | |a Stock exchanges | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Stock market indexes | ||
| 653 | |a Program trading | ||
| 700 | 1 | |a Rosillo, R |u Business Management Dept., University of Oviedo, Gijón, Asturias, Spain. rosillo@uniovi.es | |
| 700 | 1 | |a Alvarez, N |u Business Management Dept., University of Oviedo, Gijón, Asturias, Spain. rosillo@uniovi.es | |
| 700 | 1 | |a Fernández, I |u Business Management Dept., University of Oviedo, Gijón, Asturias, Spain. rosillo@uniovi.es | |
| 700 | 1 | |a Garcia, N |u Business Management Dept., University of Oviedo, Gijón, Asturias, Spain. rosillo@uniovi.es | |
| 773 | 0 | |t Proceedings on the International Conference on Artificial Intelligence (ICAI) |g (2018), p. 400 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2136876869/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2136876869/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2136876869/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |