A neurodynamic approach for solving portfolio optimisation problem in high-frequency trading based on charnes-chooper transformation

This study addresses real-time portfolio optimisation in high-frequency trading by formulating it as a single-ratio fractional programming problem. By utilising the Charnes-Cooper transformation, we convert fractional programming into non-fractional programming. Subsequently, we introduce a projecti...

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Published in:	International journal of systems science Vol. 56; no. 7; pp. 1561 - 1576
Main Authors:	Zhu, Wenli, Chen, Jia, Hu, Jin
Format:	Journal Article
Language:	English
Published:	London Taylor & Francis 19.05.2025 Taylor & Francis Ltd
Subjects:	Charnes-Cooper transformation Mathematical programming Neural networks neurodynamic optimisation Optimization Portfolio optimisation Real time Systems science
ISSN:	0020-7721, 1464-5319
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Abstract	This study addresses real-time portfolio optimisation in high-frequency trading by formulating it as a single-ratio fractional programming problem. By utilising the Charnes-Cooper transformation, we convert fractional programming into non-fractional programming. Subsequently, we introduce a projection neural network to solve this non-fractional programming efficiently. Theoretical analysis substantiates that our neural network model exhibits exponential convergence to the optimal solution of the problem, underpinning its efficacy. The numerical simulations validate the reliability and efficiency of the obtained results.
AbstractList	This study addresses real-time portfolio optimisation in high-frequency trading by formulating it as a single-ratio fractional programming problem. By utilising the Charnes-Cooper transformation, we convert fractional programming into non-fractional programming. Subsequently, we introduce a projection neural network to solve this non-fractional programming efficiently. Theoretical analysis substantiates that our neural network model exhibits exponential convergence to the optimal solution of the problem, underpinning its efficacy. The numerical simulations validate the reliability and efficiency of the obtained results.
Author	Chen, Jia Zhu, Wenli Hu, Jin
Author_xml	– sequence: 1 givenname: Wenli surname: Zhu fullname: Zhu, Wenli organization: Southwest University of Finance and Economics – sequence: 2 givenname: Jia surname: Chen fullname: Chen, Jia organization: Southwest University – sequence: 3 givenname: Jin surname: Hu fullname: Hu, Jin email: jhu@cqjtu.edu.cn organization: Chongqing Jiaotong University
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Snippet	This study addresses real-time portfolio optimisation in high-frequency trading by formulating it as a single-ratio fractional programming problem. By...
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SubjectTerms	Charnes-Cooper transformation Mathematical programming Neural networks neurodynamic optimisation Optimization Portfolio optimisation Real time Systems science
Title	A neurodynamic approach for solving portfolio optimisation problem in high-frequency trading based on charnes-chooper transformation
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