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《Probability, Uncertainty and Quantitative Risk》: 作品数：146被引量：38H指数：3; 导出分析报告; 主办单位：山东大学; 最新期次：2025年1期更多>>; 发文主题：BSDESBSDEEXPECTATIONFORWARDSTOCHASTIC更多>>; 发文领域：理学经济管理文化科学环境科学与工程更多>>; 发文基金：国家自然科学基金国家重点基础研究发展计划高等学校学科创新引智计划山东省自然科学基金更多>>

Law of large numbers for m-dependent random vectors under sublinear expectations: 《Probability, Uncertainty and Quantitative Risk》2025年第1期1-12,共12页Mingcong Wu Guanghui Cheng; funded by the National Nature Science Foundation of China(Grant No.12001128);the GuangDong Basic and Applied Basic Research Foundation(Grant No.2022A1515011899).; Sublinear expectation relaxes the linear property of classical expectation to subadditivity and positive homogeneity,which can be expressed as E(·)=sup_(θ∈θ) E_(θ)(·)for a certain set of linear expectations{E_(...; 关键词：Law of large numbers m-dependence Sublinear expectations Rate of convergence Random vectors

Non-homogeneous stochastic linear-quadratic optimal control problems with multidimensional state and regime switching: 《Probability, Uncertainty and Quantitative Risk》2025年第1期13-30,共18页Yuyang Chen Peng Luo; Financial support from the National Natural Science Foundation of China(Grant Nos.12101400 and 12326603)is gratefully acknowledged。; In this paper,we explore non-homogeneous stochastic linear-quadratic(LQ)optimal control problems with multidimensional states and regime switching.We focus on the corresponding stochastic Riccati equation(SRE),which m...; 关键词：Non-homogeneous stochastic LQ problem Regime switching Multidimensional state BSDE Unbounded coefficients

Existence, uniqueness and comparison theorem on unbounded solutions of general time-interval BSDEs with sub-quadratic generators: 《Probability, Uncertainty and Quantitative Risk》2025年第1期31-58,共28页Chuang Gu Yan Wang Shengjun Fan; This study addresses the existence, uniqueness, and comparison theorem forunbounded solutions of one-dimensional backward stochastic differential equations (BSDEs)with sub-quadratic generators, considering both finite...; 关键词：Existence and uniqueness Unboundedd solutions Backward stochastic differential equation Comparison theorem General time-interval Sub-quadratic growth

An algorithm for the calculation of upper variance under multiple probabilities and its application to quadratic programming: 《Probability, Uncertainty and Quantitative Risk》2025年第1期59-66,共8页Xinpeng Li Miao Yu Shiyi Zheng; The concept of upper variance under multiple probabilities is defined through a corresponding minimax optimization problem.This study proposes a simple algorithm to solve this optimization problem exactly.Additionally...; 关键词：Multiple probabilities Quadratic programming Sublinear expectation Upper variance

Optimal control of a class of fully coupled forward-backward stochastic partial differential equations: 《Probability, Uncertainty and Quantitative Risk》2025年第1期67-102,共36页Suya Zhang Maozhong Xu Qingxin Meng; Qingxin Meng was supported by the Key Projects of Natural Science Foundation of Zhejiang Province(Grant No.LZ22A010005);the National Natural Science Foundation of China(Grant Nos.12271158 and 11871121).; This paper investigates the optimal control problem for a class of fully coupled forward-backward stochastic partial differential equations(FBSPDEs).Based on the existence of a unique solution to such equations,we for...; 关键词：Forward-backward stochastic partial differential equation Monotonicity condition Stochastic maximum principle Convex domain Linear quadratic problem

A segment-wise dynamic programming algorithm for BSDEs|: 《Probability, Uncertainty and Quantitative Risk》2025年第1期103-134,共32页Christian Bender Steffen Meyer; We introduce and analyze a family of linear least-squares Monte Carlo schemesfor backward SDEs, which interpolate between the one-step dynamic programmingscheme of Lemor, Warin, and Gobet (Bernoulli, 2006) and the mul...; 关键词：Backward stochastic differential equations Empirical regression Dynamic programming Monte Carlo methods

Deviation bounds for the norm of a random vector under exponential moment conditions with applications: 《Probability, Uncertainty and Quantitative Risk》2025年第1期135-158,共24页Vladimir Spokoiny; Financial support by the German Research Foundation(DFG)through the Collaborative Research Center 1294"Data assimnilation"is gratefully acknowledged.; Hanson-Wright inequality provides a powerful tool for bounding the norm ||ζ|| of a centered stochastic vector ζ with independent entries and sub-gaussian behavior.This paper extends the bounds to the case when ζ on...; 关键词：Upper quantiles Phase transition Vector Bernoulli sums Frobenius loss

Invariance times transfer properties: 《Probability, Uncertainty and Quantitative Risk》2024年第4期431-452,共22页Stéphane Crepey; Invariance times are stopping times T such that local martingales with respect to some reduced filtration and an equivalently changed probability measure,stopped before T,are local martingales with respect to the orig...; 关键词：Progressive enlargement of filtration Invariance time Semimartingale calculus Markov process Backward stochastic differential equation Counterparty risk Credit risk

Exponential growth BSDE driven by a marked point process: 《Probability, Uncertainty and Quantitative Risk》2024年第4期453-498,共46页Zihao Gu Yiqing Lin Kun Xu; supported by NSFC(Grant No.12371473);by the Tianyuan Fund for Mlathematics of NSFC(Grant No.12326603)。; In this study,we investigate the well-posedness of exponential growth backward stochastic differcntial cquations(BSDEs)drivcn by a markcd point process(MPP)under unbounded terminal conditions.Our analysis utilizes a f...; 关键词：Exponential growth BSDEs Marked point processes Mean-reflected BSDEs

On the pricing and hedging of precipitation derivatives: 《Probability, Uncertainty and Quantitative Risk》2024年第4期499-528,共30页Markus Hess; In this paper,we present a new precipitation model based on a multi-factor Ornstein-Uhlenbeck approach of pure-jump type.In this setup,we derive a representation for the related precipitation swap price process and in...; 关键词：Precipitation model Precipitation swap price Minimal variance hedging.Option pricing Information premium Future information Stochastic differential equation Enlarged filtration Stochastic maximum principle Malliavin calculus Fourier transform

《Probability, Uncertainty and Quantitative Risk》