Quantum Finance: um tutorial de computação quântica aplicada ao mercado financeiro

Canabarro, Askery; Mendonça, Taysa M.; Nery, Ranieri; Moreno, George; Albino, Anton S.; F., de Jesus, Gleydson; Chaves, Rafael

doi:10.1590/1806-9126-rbef-2022-0099

Cited by 5 publications

(1 citation statement)

References 69 publications

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“…Practical implementations of quantum technologies in finance, as explored by Canabarro et al (2022) [17], Wang and Lee (2022) [18], and further discussed by Naik et al (2023) [19] and Chang et al (2023) [20], underscore the ongoing integration of quantum computing into financial practices, promising to enhance the robustness and efficiency of financial markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Quantum Temporal Winds: Turbulence in Financial Markets

Zheng,

Dong

2024

Mathematics

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This paper leverages turbulence theory from physics to examine the similarities and differences between financial market volatility and turbulent phenomena on a statistical physics level. By drawing analogies between the dynamics of financial markets and fluid turbulence, an innovative analytical framework has been developed to enhance our understanding of the complexity inherent in financial markets. The research methodology involves a comparative analysis of several national stock market indices and simulated turbulent velocity time series, with a particular focus on key statistical properties such as probability distributions, correlation structures, and power spectral densities. Furthermore, a financial market capital flow model has been established, and corresponding solutions have been proposed. Through computational simulations and data analysis, it was discovered that financial market volatility shares some statistical characteristics with turbulence, yet there are significant differences in the shape of probability distributions and the timescales of correlations. This indicates that although financial markets exhibit patterns similar to turbulence, as a multivariate-driven complex system, their behavioral patterns do not completely correspond to natural turbulence phenomena, highlighting the limitations of directly applying turbulence theory to financial market analysis. Additionally, the study explores the use of Bézier curves to simulate market volatility and, based on these analyses, formulates trading strategies that demonstrate practical applications in risk management. This research provides fresh perspectives for the fields of financial market theory and econophysics, offering new insights into the complexity of financial markets and the prevention and management of financial risks.

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Section: Literature Reviewmentioning

confidence: 99%

Quantum Temporal Winds: Turbulence in Financial Markets

Zheng,

Dong

2024

Mathematics

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A narrative review on quantum finance theory

Dong,

Zheng,

Zhu

2024

Int. J. Quantum Inform.

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This paper systematically reviews the historical development trajectory and current situation of quantum financial theory research through an in-depth review of relevant literature. This paper summarizes the history of the concept of quantum finance, elaborates on the development stages of quantum finance, and explains the contributions of representative work in different periods in various aspects, such as theoretical frameworks, mathematical models, and algorithmic tools, which is of great significance to the research path of quantum finance. In addition, the paper introduces in detail the research progress of domestic and foreign body problems, such as quantum algorithm optimization of investment portfolios, quantitative pricing of derivatives, quantum neural networks, etc., laying a good foundation for future in-depth study of this interdisciplinary subject. Overall, this paper systematically reviews the development history of quantum finance research, provides readers with a macro understanding framework by sorting out the progress in different research fields, and has significant reference value for interdisciplinary exchanges.

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Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States

Drinko,

Correr,

Medina

et al. 2024

Preprint

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Variational quantum algorithms (VQAs) have emerged in recent years as a promise to obtain quantum advantage. These task-oriented algorithms work in a hybrid loop combining a quantum processor and classical optimization. Using a specific class of VQA named variational quantum eigensolvers (VQEs), we choose some parameterized quantum circuits to benchmark them at entanglement witnessing and entangled ground state detection for many-body systems described by Heisenberg Hamiltonian, varying the number of qubits and shots. Quantum circuits whose structure is inspired by the Hamiltonian interactions presented better results on cost function estimation than problem-agnostic circuits.

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Quantum Finance: um tutorial de computação quântica aplicada ao mercado financeiro

Cited by 5 publications

References 69 publications

Quantum Temporal Winds: Turbulence in Financial Markets

Quantum Temporal Winds: Turbulence in Financial Markets

A narrative review on quantum finance theory

Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States

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