Deng Ding

Dr. Deng Ding

Faculty of Science and Technology, University of Macau, Macau SAR, China

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

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

Representative Publications

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21 November 2017 in Journal of Scientific Computing
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Journal Article
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SLSiu-Long Lei
Siu-Long Lei
WWWenfei Wang
Wenfei Wang
XCXu Chen
Xu Chen
DDDeng Ding
Deng Ding

3 January 2025 in Computational Economics
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Journal Article
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JZJirong Zhuang
Jirong Zhuang
DDDeng Ding
Deng Ding
WLWeiguo Lu
Weiguo Lu
XWXuan Wu
Xuan Wu
GYGangnan Yuan
Gangnan Yuan

2 April 2023 in Fractal and Fractional
Verified
Journal Article
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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.

18 March 2012 in Applied Mathematics-A Journal of Chinese Universities
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Journal Article
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DDDeng Ding
Deng Ding
NHNing-Ying Huang
Ning-Ying Huang
JZJing-Ya Zhao
Jing-Ya Zhao

23 January 2024 in Computational and Applied Mathematics
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Journal Article
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GYGangnan Yuan
Gangnan Yuan
DDDeng Ding
Deng Ding
WLweiguo lu
weiguo lu
FWFengyan Wu
Fengyan Wu

14 November 2018 in arXiv
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JYJuliang Yin
Juliang Yin
DDDeng Ding
Deng Ding
SKSui Yang Khoo
Sui Yang Khoo
The problem of domain aiming control is formulated for controlled stochastic nonlinear systems. This issue involves regularity of the solution to the resulting closed-loop stochastic system. To begin with, an extended existence and uniqueness theorem for stochastic differential equation with local Lipschitz coefficients is proven by using a Lyapunov-type function. A Lyapunov-based sufficient condition is also given under which there is no regularity of the solution for a class of stochastic differential equations. The notions of domain recurrence and residence time for stochastic nonlinear systems are introduced, and various criteria for the recurrence and non-recurrence relative to a bounded open domain or an unbounded domain are provided. Furthermore, upper bounds of either the expectation or the moment-generating function of the residence time are derived. In particular, a connection between the mean residence time and a Dirichlet problem is investigated and illustrated with a numerical example. Finally, the problem of domain aiming control is considered for certain types of nonlinear and linear stochastic systems. Several examples are provided to illustrate the theoretical results.