Hosseini, R.; Tajik, S.; Koohi Lai, Z.; Jamali, T.; Haven, E.; Jafari, R. Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets. Entropy2023, 25, 1061.
Hosseini, R.; Tajik, S.; Koohi Lai, Z.; Jamali, T.; Haven, E.; Jafari, R. Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets. Entropy 2023, 25, 1061.
Hosseini, R.; Tajik, S.; Koohi Lai, Z.; Jamali, T.; Haven, E.; Jafari, R. Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets. Entropy2023, 25, 1061.
Hosseini, R.; Tajik, S.; Koohi Lai, Z.; Jamali, T.; Haven, E.; Jafari, R. Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets. Entropy 2023, 25, 1061.
Abstract
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&P financial market time series to verify the presence of rare events in the non-Gaussian densities and demonstrate deviation from the Gaussian case.
Keywords
Non-Gaussian time series; MRW; Bohmian quantum; Stock market
Subject
Physical Sciences, Other
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
