Using the Quantum Potential in Elementary Portfolio Management: Some Initial Ideas

Khaksar, Hossein; Haven, Emmanuel; Nasiri, Sina; Jafari, G. R.

doi:10.3390/e23020180

Cited by 4 publications

(5 citation statements)

References 27 publications

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“…They strongly believe that in studying some of the financial and social systems, violating the laws of classical probability, a deeper uncertainty principle, relative to the uncertainty represented by classical probability theory, exists [1,2]. The number of applications from applying quantum theory to social and financial problems, ranges from cognitive science and psychology, to economy, and quantum computing for finance [3][4][5][6][7][8]. In finance, more specifically, quantum modeling of risks and decision-making to the analysis of the financial market [9][10][11][12], has concerned interest rates and option pricing [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Quantum Bohmian Inspired Potential to Model Non-Gaussian time series and its Application in Financial Markets

Hosseini¹,

Tajik²,

Lai³

et al. 2023

Preprint

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We have implemented quantum modeling mainly based on Bohmian Mechanics to study time series that contain strong coupling between their events. Compared to time series with normal densities, such time series are associated with rare events. Hence, employing Gaussian statistics drastically underestimates the occurrence of their rare events. The central objective of this study is to investigate the effects of rare events in the probability densities of time series from the point of view of quantum measurements. For this purpose, we first model the non-Gaussian behavior of time series using the multifractal random walk (MRW) approach. Then, we examine the role of the key parameter of MRW, λ, which controls the degree of non-Gaussianity, in quantum potentials derived for time series. Our Bohmian quantum analysis shows that the derived potential takes some negative values in high frequencies (its mean values), then substantially increases, and the value drops again for rare events. Thus, rare events can generate a potential barrier in the high-frequency region of the quantum potential, and the effect of such a barrier becomes prominent when the system transverses it. Finally, as an example of applying quantum potential beyond the microscopic world, we compute quantum potentials for the S&amp;P financial market time series to verify the presence of rare events in the non-Gaussian densities and demonstrate deviation from the Gaussian case.

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Section: Introductionmentioning

confidence: 99%

Quantum Bohmian Inspired Potential to Model Non-Gaussian time series and its Application in Financial Markets

Hosseini¹,

Tajik²,

Lai³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…One particle would affect others with large distances via the pilot wave field. It has been proposed that these Bohmian mechanics drawbacks will turn into benefits when they are applied to the financial market [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…From many different angles, behavioral finance can be examined. Recently, Bohmian quantum mechanics description of behavioral financial factors has been proposed [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. The Bohmian interpretation of quantum physics is frequently referred to as the hidden variables interpretation.…”

Section: Introductionmentioning

confidence: 99%

Distribution of Return Transition for Bohm-Vigier Stochastic Mechanics in Stock Market

Liu

Chang

2023

Symmetry

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The Bohm-Vigier stochastic model is assumed as a natural generalization of the Black-Scholes model in stock market. The behavioral factor of stock market recognizes as a hidden sector in Bohmian mechanics. A Fokker-Planck equation description for the Bohm-Vigier stochastic model is presented. We find the familiar Boltzmann distribution is a stationary solution of the Fokker-Planck equation for the Bohm-Vigier model. The return transition distribution of stock market, which corresponds with a time-dependent solution of the Fokker-Planck equation, is obtained.

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“…They strongly believe that, in studying some of the financial and social systems, violating the laws of classical probability, a deeper uncertainty principle, relative to the uncertainty represented by classical probability theory, exists [1,2]. The number of applications of quantum theory to social and financial problems, ranges from cognitive science and psychology, to economy, and quantum computing for finance [3][4][5][6][7][8]. In finance, more specifically, we note the quantum modeling of risks and decision-making as it can be applied to the analysis of financial markets [9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets

Hosseini

Tajik

Lai

et al. 2023

Entropy

Self Cite

View full text Add to dashboard Cite

We have implemented quantum modeling mainly based on Bohmian mechanics to study time series that contain strong coupling between their events. Compared to time series with normal densities, such time series are associated with rare events. Hence, employing Gaussian statistics drastically underestimates the occurrence of their rare events. The central objective of this study was to investigate the effects of rare events in the probability densities of time series from the point of view of quantum measurements. For this purpose, we first model the non-Gaussian behavior of time series using the multifractal random walk (MRW) approach. Then, we examine the role of the key parameter of MRW, λ, which controls the degree of non-Gaussianity, in quantum potentials derived for time series. Our Bohmian quantum analysis shows that the derived potential takes some negative values in high frequencies (its mean values), then substantially increases, and the value drops again for rare events. Thus, rare events can generate a potential barrier in the high-frequency region of the quantum potential, and the effect of such a barrier becomes prominent when the system transverses it. Finally, as an example of applying the quantum potential beyond the microscopic world, we compute quantum potentials for the S&P financial market time series to verify the presence of rare events in the non-Gaussian densities and demonstrate deviation from the Gaussian case.

show abstract

Using the Quantum Potential in Elementary Portfolio Management: Some Initial Ideas

Cited by 4 publications

References 27 publications

Quantum Bohmian Inspired Potential to Model Non-Gaussian time series and its Application in Financial Markets

Quantum Bohmian Inspired Potential to Model Non-Gaussian time series and its Application in Financial Markets

Distribution of Return Transition for Bohm-Vigier Stochastic Mechanics in Stock Market

Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets

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