By a News Reporter-Staff News Editor at Journal of Mathematics -- Research findings on Mathematics - Computational Mathematics are discussed in a new report. According to news reporting from Zhengzhou, People’s Republic of China, by VerticalNews editors, the research stated, “This paper means to price weather derivatives through solving the Partial Differential Equation (PDE) of the Ornstein-Uhlenbeck process. Since the PDE is convection dominated, a finite difference scheme with adaptively adjusted one-sided difference is proposed to discretize the PDE without causing spurious oscillations.”
The news correspondents obtained a quote from the research from the School of Mathematics and Statistics, “We compare the finite difference scheme with both the Monte Carlo simulations and Alaton’s approximate formulas. It is shown by extensive numerical experiments that the PDE based approach is accurate, efficient and practical for weather derivative pricing. In addition, we point out that the PDE approach developed for discretely sampled temperature is essentially equivalent to the Semi-Lagrangian time stepping based method.”
According to the news reporters, the research concluded: “A corresponding Semi-Lagrangian method is also proposed to price weather derivatives of continuously sampled temperature.”
For more information on this research see: Pricing weather derivatives with partial differential equations of the Ornstein-Uhlenbeck process. Computers & Mathematics with Applications , 2018;75(3):1044-1059. 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/)
Our news journalists report that additional information may be obtained by contacting P. Li, North China Univ Water Resources & Elect Power, Sch Math & Stat, Zhengzhou 450045, Henan, People’s Republic of China.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.camwa.2017.10.030. 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: (2018-04-10), Findings from School of Mathematics and Statistics Provides New Data on Computational Mathematics (Pricing weather derivatives with partial differential equations of the Ornstein-Uhlenbeck process), Journal of Mathematics, 222, ISSN: 1945-8746, BUTTER® ID: 015475395
From the newsletter Journal of Mathematics.
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