<i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations

In this paper, we study the applications of conformable backward stochastic differential equations driven by Brownian motion and compensated random measure in nonlinear expectation. From the comparison theorem, we introduce the concept of <i>g</i>-expectation and give related properties...

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Main Authors: Mei Luo, Michal Fečkan, Jin-Rong Wang, Donal O’Regan
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Axioms
Subjects:
Online Access:https://www.mdpi.com/2075-1680/11/2/75
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author Mei Luo
Michal Fečkan
Jin-Rong Wang
Donal O’Regan
author_facet Mei Luo
Michal Fečkan
Jin-Rong Wang
Donal O’Regan
author_sort Mei Luo
collection DOAJ
description In this paper, we study the applications of conformable backward stochastic differential equations driven by Brownian motion and compensated random measure in nonlinear expectation. From the comparison theorem, we introduce the concept of <i>g</i>-expectation and give related properties of <i>g</i>-expectation. In addition, we find that the properties of conformable backward stochastic differential equations can be deduced from the properties of the generator <i>g</i>. Finally, we extend the nonlinear Doob–Meyer decomposition theorem to more general cases.
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spelling doaj.art-b9cc14fef64a487f80c46fd575361ebb2023-11-23T18:47:17ZengMDPI AGAxioms2075-16802022-02-011127510.3390/axioms11020075<i>g</i>-Expectation for Conformable Backward Stochastic Differential EquationsMei Luo0Michal Fečkan1Jin-Rong Wang2Donal O’Regan3Department of Mathematics, Guizhou University, Guiyang 550025, ChinaDepartment of Mathematical Analysis and Numerical Mathematics, Comenius University in Bratislava, Mlynská dolina, 842 48 Bratislava, SlovakiaDepartment of Mathematics, Guizhou University, Guiyang 550025, ChinaSchool of Mathematical and Statistical Sciences, National University of Ireland, 999014 Galway, IrelandIn this paper, we study the applications of conformable backward stochastic differential equations driven by Brownian motion and compensated random measure in nonlinear expectation. From the comparison theorem, we introduce the concept of <i>g</i>-expectation and give related properties of <i>g</i>-expectation. In addition, we find that the properties of conformable backward stochastic differential equations can be deduced from the properties of the generator <i>g</i>. Finally, we extend the nonlinear Doob–Meyer decomposition theorem to more general cases.https://www.mdpi.com/2075-1680/11/2/75nonlinear expectation<i>g</i>-expectationDoob–Meyer decomposition theorem
spellingShingle Mei Luo
Michal Fečkan
Jin-Rong Wang
Donal O’Regan
<i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
Axioms
nonlinear expectation
<i>g</i>-expectation
Doob–Meyer decomposition theorem
title <i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
title_full <i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
title_fullStr <i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
title_full_unstemmed <i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
title_short <i>g</i>-Expectation for Conformable Backward Stochastic Differential Equations
title_sort i g i expectation for conformable backward stochastic differential equations
topic nonlinear expectation
<i>g</i>-expectation
Doob–Meyer decomposition theorem
url https://www.mdpi.com/2075-1680/11/2/75
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AT michalfeckan igiexpectationforconformablebackwardstochasticdifferentialequations
AT jinrongwang igiexpectationforconformablebackwardstochasticdifferentialequations
AT donaloregan igiexpectationforconformablebackwardstochasticdifferentialequations