Stock loan valuation based on the Finite Moment Log-Stable process
By a News Reporter-Staff News Editor at Journal of Mathematics -- Fresh data on Mathematics - Computational Mathematics are presented in a new report. According to news reporting originating from Guiyang, People’s Republic of China, by VerticalNews correspondents, research stated, “The empirical test suggests that the log-return series of stock price in US market reject the normal distribution and admit instead a subclass of the asymmetric distribution. In this paper, we investigate the stock loan problem under the assumption that the return of stock follows the finite moment log-stable process (FMLS).”
Financial supporters for this research include Fundamental Research Funds for the Central Universities, National Natural Science Foundation of China.
Our news editors obtained a quote from the research from the School of Finance, “In this case, the pricing model of stock loan can be described by a space-fractional partial differential equation with time-varying free boundary condition. Firstly, a penalty term is introduced to change the original problem to be defined on a fixed domain, and then a fully-implicit difference scheme has been developed. Secondly, based on the fully-implicit scheme, we prove that the stock loan value generated by the penalty method cannot fall below the value obtained when the stock loan is exercised early. Thirdly, the numerical experiments are carried out to demonstrate differences of stock loan model under the FMLS and the standard normal distribution. Optimal redemption strategy of stock loan has been achieved.”
According to the news editors, the research concluded: “Furthermore the impact of key parameters in our model on the stock loan evaluation are analyzed, and some reasonable explanation are given.”
For more information on this research see: Stock loan valuation based on the Finite Moment Log-Stable process. Computers & Mathematics with Applications , 2018;75(2):374-387. Computers & Mathematics with Applications can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Computers & Mathematics with Applications - http://www.journals.elsevier.com/computers-and-mathematics-with-applications/)
The news editors report that additional information may be obtained by contacting C.Y. Fan, Guizhou Univ Commerce, Sch Finance, Guiyang 550014, Guizhou, People’s Republic of China. Additional authors for this research include K.L. Xiang and S.Z. Chen.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.camwa.2017.09.015. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-04-17), Findings from School of Finance Provides New Data about Computational Mathematics (Stock loan valuation based on the Finite Moment Log-Stable process), Journal of Mathematics, 250, ISSN: 1945-8746, BUTTER® ID: 015518451
From the newsletter Journal of Mathematics.
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