11 results on '"Miryana Grigorova"'
Search Results
2. Optimal stopping with f-expectations: The irregular case
- Author
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Miryana Grigorova, Youssef Ouknine, Peter Imkeller, and Marie-Claire Quenez
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Statistics and Probability ,Comparison theorem ,Applied Mathematics ,Infinitesimal ,010102 general mathematics ,Optional stopping theorem ,01 natural sciences ,Dynamic risk measure ,010104 statistics & probability ,Modeling and Simulation ,Snell envelope ,Filtration (mathematics) ,Applied mathematics ,Optimal stopping ,0101 mathematics ,Nonlinear expectation ,Mathematical economics ,Mathematics - Abstract
We consider the optimal stopping problem with non-linear $f$-expectation (induced by a BSDE) without making any regularity assumptions on the reward process $\xi$. and with general filtration. We show that the value family can be aggregated by an optional process $Y$. We characterize the process $Y$ as the $\mathcal{E}^f$-Snell envelope of $\xi$. We also establish an infinitesimal characterization of the value process $Y$ in terms of a Reflected BSDE with $\xi$ as the obstacle. To do this, we first establish a comparison theorem for irregular RBSDEs. We give an application to the pricing of American options with irregular pay-off in an imperfect market model.
- Published
- 2020
3. European options in a non-linear incomplete market model with default
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Miryana Grigorova, Marie-Claire Quenez, Agnès Sulem, School of Mathematics [Leeds], University of Leeds, Laboratoire de Probabilités, Statistiques et Modélisations (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Mathematical Risk Handling (MATHRISK), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), School of Mathematics - University of Leeds, Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Inria de Paris, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM)
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Incomplete market ,Numerical Analysis ,Computer Science::Computer Science and Game Theory ,Non-linear optional decomposition ,[QFIN]Quantitative Finance [q-fin] ,[QFIN.PR]Quantitative Finance [q-fin]/Pricing of Securities [q-fin.PR] ,Applied Mathematics ,010102 general mathematics ,f-expectation ,BSDEs with constraints ,Non-linear pricing ,European options ,Pricing-hedging duality ,01 natural sciences ,[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,Control problems with non-linear expectation ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,010104 statistics & probability ,[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] ,0101 mathematics ,Superhedging ,Finance - Abstract
International audience; This paper studies the superhedging prices and the associated superhedging strategies for European options in a non-linear incomplete market model with default. We present the seller's and the buyer's point of view. The underlying market model consists of a risk-free asset and a risky asset driven by a Brownian motion and a compensated default martingale. The portfolio processes follow non-linear dynamics with a non-linear driver f. By using a dynamic programming approach, we first provide a dual formulation of the seller's (superhedging) price for the European option as the supremum, over a suitable set of equivalent probability measures Q ∈ Q, of the f-evaluation/expectation under Q of the payoff. We also provide a characterization of the seller's (superhedging) price process as the minimal supersolution of a constrained BSDE with default and a characterization in terms of the minimal weak supersolution of a BSDE with default. By a form of symmetry, we derive corresponding results for the buyer. Our results rely on first establishing a non-linear optional and a non-linear predictable decomposition for processes which are $\mathcal{E}^f$-strong supermartingales under Q, for all Q ∈ Q.
- Published
- 2020
4. On the strict value of the non-linear optimal stopping problem
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Marie-Claire Quenez, Miryana Grigorova, Peter Imkeller, and Youssef Ouknine
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Statistics and Probability ,irregular payoff ,strong $\mathcal {E}^{f}$-supermartingale ,Process (computing) ,Nonlinear system ,general filtration ,optimal stopping ,non-linear expectation ,strict value process ,60G07 ,91G80 ,Filtration (mathematics) ,Applied mathematics ,Optimal stopping ,Statistics, Probability and Uncertainty ,Value (mathematics) ,60G40 ,Mathematics - Abstract
We address the non-linear strict value problem in the case of a general filtration and a completely irregular pay-off process $(\xi _{t})$. While the value process $(V_{t})$ of the non-linear problem is only right-uppersemicontinuous, we show that the strict value process $(V^{+}_{t})$ is necessarily right-continuous. Moreover, the strict value process $(V_{t}^{+})$ coincides with the process of right-limits $(V_{t+})$ of the value process. As an auxiliary result, we obtain that a strong non-linear $f$-supermartingale is right-continuous if and only if it is right-continuous along stopping times in conditional $f$-expectation.
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- 2020
5. Doubly Reflected BSDEs and $\mathcal{E} ^{{f}}$-Dynkin games: beyond the right-continuous case
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Youssef Ouknine, Marie-Claire Quenez, Peter Imkeller, and Miryana Grigorova
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Statistics and Probability ,Pure mathematics ,47N10 ,Physical constant ,stopping time ,Characterization (mathematics) ,01 natural sciences ,Combinatorics ,010104 statistics & probability ,general filtration ,60G07 ,Stopping time ,Saddle point ,Uniqueness ,0101 mathematics ,60G40 ,Mathematics ,nonlinear expectation ,game option ,010102 general mathematics ,stopping system ,cancellable American option ,93E20 ,saddle points ,Extension (predicate logic) ,$f$-expectation ,backward stochastic differential equations ,Dynkin game ,doubly reflected BSDEs ,Statistics, Probability and Uncertainty ,60H30 ,Nonlinear expectation ,Value (mathematics) - Abstract
We formulate a notion of doubly reflected BSDE in the case where the barriers $\xi $ and $\zeta $ do not satisfy any regularity assumption and with general filtration. Under a technical assumption (a Mokobodzki-type condition), we show existence and uniqueness of the solution. In the case where $\xi $ is right upper-semicontinuous and $\zeta $ is right lower-semicontinuous, the solution is characterized in terms of the value of a corresponding $\boldsymbol{\mathcal {E}} ^f$-Dynkin game, i.e. a game problem over stopping times with (non-linear) $f$-expectation, where $f$ is the driver of the doubly reflected BSDE. In the general case where the barriers do not satisfy any regularity assumptions, the solution of the doubly reflected BSDE is related to the value of “an extension” of the previous non-linear game problem over a larger set of “stopping strategies” than the set of stopping times. This characterization is then used to establish a comparison result and a priori estimates with universal constants.
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- 2018
6. BSDEs with Default Jump
- Author
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Marie Claire Quenez, Roxana Dumitrescu, Miryana Grigorova, and Agnès Sulem
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Comparison theorem ,Stochastic differential equation ,Probability of default ,Semimartingale ,Special case ,Conditional expectation ,Martingale (probability theory) ,Mathematical economics ,Brownian motion ,Mathematics - Abstract
We study (nonlinear) Backward Stochastic Differential Equations (BSDEs) driven by a Brownian motion and a martingale attached to a default jump with intensity process λ = (λ t). The driver of the BSDEs can be of a generalized form involving a singular optional finite variation process. In particular, we provide a comparison theorem and a strict comparison theorem. In the special case of a generalized λ-linear driver, we show an explicit representation of the solution, involving conditional expectation and an adjoint exponential semimartingale; for this representation, we distinguish the case where the singular component of the driver is predictable and the case where it is only optional. We apply our results to the problem of (nonlinear) pricing of European contingent claims in an imperfect market with default. We also study the case of claims generating intermediate cashflows, in particular at the default time, which are modeled by a singular optional process. We give an illustrating example when the seller of the European option is a large investor whose portfolio strategy can influence the probability of default.
- Published
- 2018
7. Optimal stopping and a non-zero-sum Dynkin game in discrete time with risk measures induced by BSDEs
- Author
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Marie-Claire Quenez, Miryana Grigorova, Benassù, Serena, Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Institut für Mathematik [Humboldt], Humboldt University Of Berlin, and Humboldt-Universität zu Berlin
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Statistics and Probability ,Mathematical optimization ,[MATH.MATH-PR] Mathematics [math]/Probability [math.PR] ,Computer Science::Computer Science and Game Theory ,non-zero-sum Dynkin game ,g-expectation ,[QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,01 natural sciences ,[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,Nash equilibrium ,Dynamic risk measure ,FOS: Economics and business ,010104 statistics & probability ,symbols.namesake ,Stopping time ,FOS: Mathematics ,Optimal stopping ,0101 mathematics ,ComputingMilieux_MISCELLANEOUS ,Mathematics ,game option ,010102 general mathematics ,Stochastic game ,Probability (math.PR) ,dynamic risk measure ,Lipschitz continuity ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,Discrete time and continuous time ,Zero-sum game ,optimal stopping ,Modeling and Simulation ,Risk Management (q-fin.RM) ,symbols ,Mathematics - Probability ,Quantitative Finance - Risk Management - Abstract
International audience; We first study an optimal stopping problem in which a player (an agent) uses a discrete stopping time in order to stop optimally a payoff process whose risk is evaluated by a (non-linear) $g$-expectation. We then consider a non-zero-sum game on discrete stopping times with two agents who aim at minimizing their respective risks. The payoffs of the agents are assessed by g-expectations (with possibly different drivers for the different players). By using the results of the first part, combined with some ideas of S. Hamadène and J. Zhang, we construct a Nash equilibrium point of this game by a recursive procedure. Our results are obtained in the case of a standard Lipschitz driver $g$ without any additional assumption on the driver besides that ensuring the monotonicity of the corresponding $g$-expectation.
- Published
- 2017
8. Reflected BSDEs when the obstacle is not right-continuous and optimal stopping
- Author
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Marie-Claire Quenez, Miryana Grigorova, Youssef Ouknine, Elias R. Offen, Peter Imkeller, Institut für Mathematik [Humboldt], Humboldt-Universität zu Berlin, University of Botswana, Université Cadi Ayyad [Marrakech] (UCA), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Humboldt University Of Berlin
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Statistics and Probability ,Pure mathematics ,Generalization ,47N10 ,Banach space ,strong $\mathcal{E}^{f}$-supermartingale ,backward stochastic differential equation ,Computational Finance (q-fin.CP) ,Mertens decomposition ,[QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,01 natural sciences ,[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,Dynamic risk measure ,FOS: Economics and business ,010104 statistics & probability ,Stochastic differential equation ,Quantitative Finance - Computational Finance ,Bellman equation ,60G07 ,Mertens decomposition,reflected backward stochastic differential equation,optimal stopping,dynamic risk measure,f -expectation,strong optional supermartingale,backward stochastic differential equation ,FOS: Mathematics ,Optimal stopping ,Uniqueness ,0101 mathematics ,60G40 ,Mathematics ,010102 general mathematics ,strong optional supermartingale ,Probability (math.PR) ,Mertens’ decomposition ,93E20 ,dynamic risk measure ,Lipschitz continuity ,$f$-expectation ,f -expectation ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,reflected backward stochastic differential equation ,optimal stopping ,Risk Management (q-fin.RM) ,Statistics, Probability and Uncertainty ,60H30 ,Mathematics - Probability ,Quantitative Finance - Risk Management - Abstract
International audience; In the first part of the paper, we study reflected backward stochastic differential equations (RBSDEs) with lower obstacle which is assumed to be right upper-semicontinuous but not necessarily right-continuous. We prove existence and uniqueness of the solutions to such RBSDEs in appropriate Banach spaces. The result is established by using some tools from the general theory of processes such as Mertens decomposition of optional strong (but not necessarily right-continuous) supermartingales, some tools from optimal stopping theory, as well as an appropriate generalization of Itô's formula due to Gal'chouk and Lenglart. In the second part of the paper, we provide some links between the RBSDE studied in the first part and an optimal stopping problem in which the risk of a financial position $\xi$ is assessed by an $f$-conditional expectation $\mathcal{E}^f(\cdot)$ (where $f$ is a Lipschitz driver). We characterize the "value function" of the problem in terms of the solution to our RBSDE. Under an additional assumption of left upper-semicontinuity on $\xi$, we show the existence of an optimal stopping time. We also provide a generalization of Mertens decomposition to the case of strong $\mathcal{E}^f$-supermartingales.
- Published
- 2015
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9. Stochastic orderings with respect to a capacity and an application to a financial optimization problem
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Miryana Grigorova, Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Grigorova, Miryana
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Statistics and Probability ,stochastic orderings,increasing convex stochastic dominance,Choquet integral,quantile function with respect to a capacity,stop-loss ordering,Choquet expected utility,distorted capacity,generalized Hardy-Littlewood's inequalities,distortion risk measure,ambiguity ,Mathematical optimization ,[MATH.MATH-PR] Mathematics [math]/Probability [math.PR] ,generalized Hardy-Littlewood's inequalities ,Logarithmically concave function ,Stochastic dominance ,increasing convex stochastic dominance ,[QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,quantile function with respect to a capacity ,Distortion risk measure ,Applied mathematics ,[QFIN.RM] Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,ComputingMilieux_MISCELLANEOUS ,Probability measure ,Mathematics ,[QFIN.CP] Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH] ,Quantile function ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,Monotone polygon ,stop-loss ordering ,Choquet integral ,Set function ,Modeling and Simulation ,distortion risk measure ,ambiguity ,Statistics, Probability and Uncertainty ,stochastic orderings ,distorted capacity ,Choquet expected utility - Abstract
By analogy with the classical case of a probability measure, we extend the notion of increasing convex (concave) stochastic dominance relation to the case of a normalized monotone (but not necessarily additive) set function also called a capacity. We give different characterizations of this relation establishing a link to the notions of distribution function and quantile function with respect to the given capacity. The Choquet integral is extensively used as a tool. In the second part of the paper, we give an application to a financial optimization problem whose constraints are expressed by means of the increasing convex stochastic dominance relation with respect to a capacity. The problem is solved by using, among other tools, a result established in our previous work, namely a new version of the classical upper (resp. lower) Hardy–Littlewood's inequality generalized to the case of a continuous from below concave (resp. convex) capacity. The value function of the optimization problem is interpreted in terms of risk measures (or premium principles).
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- 2014
10. Hardy-Littlewood's inequalities in the case of a capacity
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Miryana Grigorova, Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Pierre et Marie Curie - Paris 6 (UPMC), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)
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Inequality ,media_common.quotation_subject ,010102 general mathematics ,General Medicine ,01 natural sciences ,Submodular set function ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,Monotone polygon ,Set function ,0103 physical sciences ,010307 mathematical physics ,0101 mathematics ,Mathematical economics ,ComputingMilieux_MISCELLANEOUS ,Mathematics ,media_common ,Probability measure - Abstract
Hardy–Littlewoodʼs inequalities, well known in the case of a probability measure, are extended to the case of a monotone (but not necessarily additive) set function, called a capacity. The upper inequality is established in the case of a capacity assumed to be continuous and submodular, the lower — under assumptions of continuity and supermodularity.
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- 2013
11. Stochastic dominance with respect to a capacity and risk measures
- Author
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Miryana Grigorova, Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Grigorova, Miryana
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Statistics and Probability ,Mathematical optimization ,[MATH.MATH-PR] Mathematics [math]/Probability [math.PR] ,Stochastic dominance ,[QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,01 natural sciences ,[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,010104 statistics & probability ,stochastic orderings with respect to a capacity ,Choquet integral,stochastic orderings with respect to a capacity,distortion risk measure,quantile function with respect to a capacity,distorted capacity,Choquet expected utility,ambiguity,non-additive probability,Value at Risk,Rank-dependent expected utility,behavioural finance,maximal correlation risk measure,quantile-based risk measure,Kusuoka's characterization theorem ,Kusuoka's characterization theorem ,0502 economics and business ,quantile function with respect to a capacity ,Distortion risk measure ,[QFIN.RM] Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,Value at Risk ,maximal correlation risk measure ,0101 mathematics ,Rank-dependent expected utility ,Mathematics ,050208 finance ,[QFIN.CP] Quantitative Finance [q-fin]/Computational Finance [q-fin.CP] ,05 social sciences ,behavioural finance ,Quantile function ,Tail value at risk ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,Choquet integral ,Set function ,Modeling and Simulation ,Bounded function ,distortion risk measure ,non-additive probability ,ambiguity ,Statistics, Probability and Uncertainty ,distorted capacity ,Mathematical economics ,Choquet expected utility ,quantile-based risk measure - Abstract
Pursuing our previous work in which the classical notion of increasing convex stochastic dominance relation with respect to a probability has been extended to the case of a normalised monotone (but not necessarily additive) set function also called a capacity, the present paper gives a generalization to the case of a capacity of the classical notion of increasing stochastic dominance relation. This relation is characterized by using the notions of distribution function and quantile function with respect to the given capacity. Characterizations, involving Choquet integrals with respect to a distorted capacity, are established for the classes of monetary risk measures (defined on the space of bounded real-valued measurable functions) satisfying the properties of comonotonic additivity and consistency with respect to a given generalized stochastic dominance relation. Moreover, under suitable assumptions, a "Kusuoka-type" characterization is proved for the class of monetary risk measures having the properties of comonotonic additivity and consistency with respect to the generalized increasing convex stochastic dominance relation. Generalizations to the case of a capacity of some well-known risk measures (such as the Value at Risk or the Tail Value at Risk) are provided as examples. It is also established that some well-known results about Choquet integrals with respect to a distorted probability do not necessarily hold true in the more general case of a distorted capacity.
- Published
- 2011
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