Fengyan Wu

Dr. Fengyan Wu

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2022 in Chaos: An Interdisciplinary Journal of Nonlinear Science
Verified
Journal Article
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GYGangnan Yuan
Gangnan Yuan
DDDeng Ding
Deng Ding
JDJinqiao Duan
Jinqiao Duan
WLweiguo lu
weiguo lu
FWFengyan Wu
Fengyan Wu
During the COVID-19 pandemic, many institutions have announced that their counterparties are struggling to fulfill contracts. Therefore, it is necessary to consider the counterparty default risk when pricing options. After the 2008 financial crisis, a variety of value adjustments have been emphasized in the financial industry. The total value adjustment (XVA) is the sum of multiple value adjustments, which is also investigated in many stochastic models, such as the Heston [B. Salvador and C. W. Oosterlee, Appl. Math. Comput. 391, 125489 (2020)] and Bates [L. Goudenège et al., Comput. Manag. Sci. 17, 163–178 (2020)] models. In this work, a widely used pure jump Lévy process, the Carr–Geman–Madan–Yor process has been considered for pricing a Bermudan option with various value adjustments. Under a pure jump Lévy process, the value of derivatives satisfies a fractional partial differential equation (FPDE). Therefore, we construct a method that combines Monte Carlo with a finite difference of FPDE to find the numerical approximation of exposure and compare it with the benchmark Monte Carlo simulation and Fourier-cosine series method. We use the discrete energy estimate method, which is different from the existing works, to derive the convergence of the numerical scheme. Based on the numerical results, the XVA is computed by the financial exposure of the derivative value.

27 March 2018 in Boundary Value Problems
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Journal Article
Open access
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XCXiujun Cheng
Xiujun Cheng
FWFengyan Wu
Fengyan Wu
In this paper, several different conserving compact finite difference schemes are developed for solving a class of nonlinear Schrödinger equations with wave operator. It is proved that the numerical solutions are bounded and the numerical methods can achieve a convergence rate of $\mathcal{O}(\tau^{2} + h^{4})$ in the maximum norm. Moreover, by applying Richardson extrapolation, the proposed methods have a convergence rate of $\mathcal{O}(\tau^{4} + h^{4})$ in the maximum norm. Finally, several numerical experiments are presented to illustrate the theoretical results.

1 May 2019 in Applied Mathematics and Computation
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Journal Article
Closed access
XCXiaoli Chen
Xiaoli Chen
FWFengyan Wu
Fengyan Wu
JDJinqiao Duan
Jinqiao Duan
JKJürgen Kurths
Jürgen Kurths
XLXiaofan Li
Xiaofan Li

5 March 2021 in Journal of Scientific Computing
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Journal Article
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HQHongyu Qin
Hongyu Qin
FWFengyan Wu
Fengyan Wu
JZJiwei Zhang
Jiwei Zhang
CMChunlai Mu
Chunlai Mu

1 April 2018 in Applied Mathematics and Computation
Verified
Journal Article
Closed access
FWFengyan Wu
Fengyan Wu
Dongfang LiDongfang Li
Dongfang Li
Jinming WenJinming Wen
Jinming Wen
JDJinqiao Duan
Jinqiao Duan

2 April 2023 in Fractal and Fractional
Verified
Journal Article
Open access
PDF file
FWFengyan Wu
Fengyan Wu
DDDeng Ding
Deng Ding
JYJuliang Yin
Juliang Yin
WLweiguo lu
weiguo lu
GYGangnan Yuan
Gangnan Yuan
Counterparty credit risk (CCR) is a significant risk factor that financial institutions have to consider in today’s context, and the COVID-19 pandemic and military conflicts worldwide have heightened concerns about potential default risk. In this work, we investigate the changes in the value of financial derivatives due to counterparty default risk, i.e., total value adjustment (XVA). We perform the XVA for multi-asset option based on the multivariate Carr–Geman–Madan–Yor (CGMY) processes, which can be applied to a wider range of financial derivatives, such as basket options, rainbow options, and index options. For the numerical methods, we use the Monte Carlo method in combination with the alternating direction implicit method (MC-ADI) and the two-dimensional Fourier cosine expansion method (MC-CC) to find the risk exposure and make value adjustments for multi-asset derivatives.