多维BSDEs的表示定理、生存性及其应用

IF 1 2区 数学 Q3 STATISTICS & PROBABILITY Probability Uncertainty and Quantitative Risk Pub Date : 2023-01-01 DOI:10.3934/puqr.2023017
Xuejun Shi, Long Jiang
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引用次数: 0

摘要

后向随机微分方程的表示定理和生存性在理论和实际应用中都有广泛的应用,需要进一步研究。在本研究中,我们给出了一个长期存在的开放性问题,即在平方可积性和Lipschitzian连续性的标准假设下,表示定理在L^2 -意义上是否仍然成立。在此过程中,考虑了多维情况。在此基础上,利用表示定理,得到了在发生器上标准条件下BSDEs生存性的一个充分必要条件。这就消除了对生成器对时间变量具有较强的可积性和连续性的要求。作为这些结果的应用,我们对多维BSDEs的解进行了各种类型的比较和反向比较,得到了多维$ g $ -期望的若干性质。
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Representation theorem and viability property for multidimensional BSDEs and their applications
The representation theorem and the viability property for backward stochastic differential equations (BSDEs) require further exploration, given their widespread use in both theory and practical applications. In this study, we present a positive answer to the long-standing open question of whether the representation theorem still holds in the $ L^2 $ -sense under the standard assumptions of square integrability and Lipschitzian continuity on the generators of BSDEs. In the process, the multidimensional case is considered. Subsequently, based on the representation theorem, we obtain a necessary and sufficient condition for the viability property of the BSDEs under standard conditions on the generators. This removes the requirement for the generator to possess the properties of stronger integrability and continuity with respect to time variables. As an application of these results, we conduct various types of comparisons and converse comparisons for the solutions of multidimensional BSDEs, and several properties of the multidimensional $ g $ -expectation are obtained.
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来源期刊
CiteScore
1.60
自引率
13.30%
发文量
29
审稿时长
12 weeks
期刊介绍: Probability, Uncertainty and Quantitative Risk (PUQR) is a quarterly academic journal under the supervision of the Ministry of Education of the People's Republic of China and hosted by Shandong University, which is open to the public at home and abroad (ISSN 2095-9672; CN 37-1505/O1). Probability, Uncertainty and Quantitative Risk (PUQR) mainly reports on the major developments in modern probability theory, covering stochastic analysis and statistics, stochastic processes, dynamical analysis and control theory, and their applications in the fields of finance, economics, biology, and computer science. The journal is currently indexed in ESCI, Scopus, Mathematical Reviews, zbMATH Open and other databases.
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