Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm
Quantitative trading is an integral part of financial markets with high calculation speed requirements, while no quantum algorithms have been introduced into this field yet. We propose quantum algorithms for high-frequency statistical arbitrage trading by utilizing variable time condition number est...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2022-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/ac7f26 |
| _version_ | 1827871017467379712 |
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| author | Xi-Ning Zhuang Zhao-Yun Chen Yu-Chun Wu Guo-Ping Guo |
| author_facet | Xi-Ning Zhuang Zhao-Yun Chen Yu-Chun Wu Guo-Ping Guo |
| author_sort | Xi-Ning Zhuang |
| collection | DOAJ |
| description | Quantitative trading is an integral part of financial markets with high calculation speed requirements, while no quantum algorithms have been introduced into this field yet. We propose quantum algorithms for high-frequency statistical arbitrage trading by utilizing variable time condition number estimation and quantum linear regression. The algorithm complexity has been reduced from the classical benchmark O ( N ^2 d ) to $O(\sqrt{dN}{\kappa }_{0}^{2}\,\mathrm{log}{(1/{\epsilon})}^{2})\left.\right)$ , where N is the length of trading data, and d is the number of stocks, κ _0 is the condition number and ϵ is the desired precision. Moreover, two tool algorithms for condition number estimation and cointegration test are developed. |
| first_indexed | 2024-03-12T16:04:59Z |
| format | Article |
| id | doaj.art-d7e7278de01641658f3fe7b78453edfb |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:04:59Z |
| publishDate | 2022-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-d7e7278de01641658f3fe7b78453edfb2023-08-09T14:26:02ZengIOP PublishingNew Journal of Physics1367-26302022-01-0124707303610.1088/1367-2630/ac7f26Quantum computational quantitative trading: high-frequency statistical arbitrage algorithmXi-Ning Zhuang0https://orcid.org/0000-0001-5118-5066Zhao-Yun Chen1https://orcid.org/0000-0002-5181-160XYu-Chun Wu2https://orcid.org/0000-0002-8997-3030Guo-Ping Guo3https://orcid.org/0000-0002-2179-9507Origin Quantum Computing , Hefei, People’s Republic of China; CAS Key Laboratory of Quantum Information, University of Science and Technology of China , Hefei 230026, People’s Republic of ChinaInstitute of Artificial Intelligence , Hefei Comprehensive National Science Center, Hefei 230088, People’s Republic of ChinaCAS Key Laboratory of Quantum Information, University of Science and Technology of China , Hefei 230026, People’s Republic of China; Institute of Artificial Intelligence , Hefei Comprehensive National Science Center, Hefei 230088, People’s Republic of China; CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China , Hefei 230026, People’s Republic of China; Hefei National Laboratory, University of Science and Technology of China , Hefei 230088, People’s Republic of ChinaOrigin Quantum Computing , Hefei, People’s Republic of China; CAS Key Laboratory of Quantum Information, University of Science and Technology of China , Hefei 230026, People’s Republic of China; Institute of Artificial Intelligence , Hefei Comprehensive National Science Center, Hefei 230088, People’s Republic of China; CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China , Hefei 230026, People’s Republic of China; Hefei National Laboratory, University of Science and Technology of China , Hefei 230088, People’s Republic of ChinaQuantitative trading is an integral part of financial markets with high calculation speed requirements, while no quantum algorithms have been introduced into this field yet. We propose quantum algorithms for high-frequency statistical arbitrage trading by utilizing variable time condition number estimation and quantum linear regression. The algorithm complexity has been reduced from the classical benchmark O ( N ^2 d ) to $O(\sqrt{dN}{\kappa }_{0}^{2}\,\mathrm{log}{(1/{\epsilon})}^{2})\left.\right)$ , where N is the length of trading data, and d is the number of stocks, κ _0 is the condition number and ϵ is the desired precision. Moreover, two tool algorithms for condition number estimation and cointegration test are developed.https://doi.org/10.1088/1367-2630/ac7f26quantum computationstatistical arbitragequantitative tradingquantum finance |
| spellingShingle | Xi-Ning Zhuang Zhao-Yun Chen Yu-Chun Wu Guo-Ping Guo Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm New Journal of Physics quantum computation statistical arbitrage quantitative trading quantum finance |
| title | Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm |
| title_full | Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm |
| title_fullStr | Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm |
| title_full_unstemmed | Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm |
| title_short | Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm |
| title_sort | quantum computational quantitative trading high frequency statistical arbitrage algorithm |
| topic | quantum computation statistical arbitrage quantitative trading quantum finance |
| url | https://doi.org/10.1088/1367-2630/ac7f26 |
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