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Quantum prediction GJR model and its applications
Author(s) -
Wang Feixing,
Wang Yingshuai
Publication year - 2014
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/stan.12029
Subject(s) - quantum , financial market , stock market , computer science , mathematics , statistical physics , mathematical economics , finance , quantum mechanics , economics , physics , geography , context (archaeology) , archaeology
In this paper, a new statistical method to deal with the quantum finance is proposed. Through analyzing the stock data of China Mobile Communication Corporation, we discover its quantum financial effect, and then we innovate the method of testing the existence of the quantum financial effect. Furthermore, the classical normal process of the Glosten–Jagannathan–Runkle (GJR) model has been changed into the quantum wave‐function distribution, which is based on the ‘one‐dimensional infinitely deep square potential well’. The research shows that the quantum GJR model can reveal the interior uncertainty of the financial market and has a better prediction availability.