| DC Field | Value | Language |
|---|
| dc.contributor.author | Sviridenko, E. V. | - |
| dc.contributor.author | Filipchenkov, V. D. | - |
| dc.contributor.author | Zuyonok, R. V. | - |
| dc.coverage.spatial | Минск | - |
| dc.date.accessioned | 2022-10-11T08:48:30Z | - |
| dc.date.available | 2022-10-11T08:48:30Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Sviridenko, E. V. Machine learning algorithms in pair trading / Sviridenko E. V., Filipchenkov V. D., Zuyonok R. V. // Проблемы экономики и информационных технологий : сборник тезисов и статей докладов 58-ой научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 18–22 апреля 2022 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2022. – С. 73–79. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/48532 | - |
| dc.description.abstract | Pairs trading is an approach of identification and construction of mean-reverting portfolio consisting of two or more assets. We have reviewed existing literature related to the usage of machine learning algorithms in statistical arbitrage trading strategy. Additionaly, we backtested trading-pairs, that were formed with clustering and dimension reduction algorithms, using 10 years (2012–2022) of S&P stock index time-series daily market data. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | pairs trading | ru_RU |
| dc.subject | machine learning | ru_RU |
| dc.subject | statistical arbitrage | ru_RU |
| dc.subject | hiearchical agglomerative clustering | ru_RU |
| dc.subject | financial modeling | ru_RU |
| dc.title | Machine learning algorithms in pair trading | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | Проблемы экономики и информационных технологий : материалы 58-й научной конференции аспирантов, магистрантов и студентов (2022)
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