Probability, Uncertainty and Quantitative Risk

Aims & Scope

Probability, Uncertainty and Quantitative Risk (PUQR) aims to report significant developments in modern probability theory, its relation to stochastic analysis and statistics, stochastic processes, their dynamics and control, as well as applications in domains such as finance, economics, biology, computer science, and the corresponding data analysis.

The primary objective of PUQR is to publish work of the highest standards on: Ambiguity and Knightian Uncertainty, Backward stochastic differential equations, nonlinear expectation, and path-dependent PDEs, Dynamic risk measures, Mathematical modelling under uncertainty, Quantitative risks, Recursive Utility, Uncertainty quantification, Computational aspects and numerical methods related to the above topics, Related topics, among them also relevant to statistics.

The related topics encompass a broad range of research, from mathematical approaches in which the above topics play a key role or constitute an important tool, to backward SDE methods in stochastic control problems, differential games in the context of uncertainty that may, e.g., be related to asymmetric information, and to a vast field of applications such as mean-field approaches in finance or modelling systematic risk.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	0.394

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	13

Impact Factor

Year	Value
2024	1.00

Journal Rank

Year	Value
2024	13946

Journal Citation Indicator

Year	Value
2024	66

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Decision Sciences and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• On the laws of the iterated logarithm under sub-linear expectations

  Citation: 21

  Authors: Li-Xin

• Optimal unbiased estimation for maximal distribution

  Citation: 13

  Authors: Hanqing, Shige

• Convergence of the Deep BSDE method for FBSDEs with non-Lipschitz coefficients

  Citation: 9

  Authors: Yifan, Jinfeng

• Extended conditional <i>G</i>-expectations and related stopping times

  Citation: 9

  Authors: Mingshang, Shige

• Stein’s method for the law of large numbers under sublinear expectations

  Citation: 7

  Authors: Yongsheng

• Convergence rate of Peng’s law of large numbers under sublinear expectations

  Citation: 7

  Authors: Mingshang, Xiaojuan, Xinpeng

• Explicit solutions for a class of nonlinear BSDEs and their nodal sets

  Citation: 6

  Authors: Zengjing, Shuhui, Zhongmin, Xingcheng

• A universal robust limit theorem for nonlinear Lévy processes under sublinear expectation

  Citation: 5

  Authors: Mingshang, Lianzi, Gechun, Shige

• Non-linear affine processes with jumps

  Citation: 5

  Authors: Francesca, Georg, Katharina

• Existence, uniqueness and strict comparison theorems for BSDEs driven by RCLL martingales

  Citation: 5

  Authors: Tianyang, Marek

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