Linear Volterra backward stochastic integral equations

We present an explicit solution triplet $(Y,Z,K)$ to the backward stochastic Volterra integral equation (BSVIE) of linear type, driven by a Brownian motion and a compensated Poisson random measure. The process $Y$ is expressed by an integral whose kernel is explicitly given. The processes $Z$ and $K$ are expressed by Hida–Malliavin derivatives involving $Y$.     

On a class of backward stochastic Volterra integral equations

In this paper, under some restrictions of the time interval, we compare a class of backward stochastic Volterra integral equations with the corresponding simpler one; to be precise, we give the relations between their solutions under global and local Lipschitz conditions on their generator functions. Using these relations, it could be easier to study solutions of more complex equations, where coefficients in backward integrals could be treated as perturbations.     

L p solutions of backward stochastic Volterra integral equations

This paper is devoted to the unique solvability of backward stochastic Volterra integral equations (BSVIEs, for short), in terms of both M-solution and the adapted solutions. We prove the existence and uniqueness of M-solutions of BSVIEs in L ^p (1 < p < 2), which extends the existing results on M-solutions. The unique solvability of adapted solutions of BSVIEs in L ^p (p > 1) is also considered, which also generalizes the results in the existing literature.     

Continuous-time dynamic risk measures by backward stochastic Volterra integral equations

Continuous-time dynamic convex and coherent risk measures are introduced. To obtain existence of such risk measures, backward stochastic Volterra integral equations (BSVIEs, for short) are studied. For such equations, notion of adapted M-solution is introduced, well-posedness is established, duality principles and comparison theorems are presented. Then a class of dynamic convex and coherent risk measures are identified as a component of the adapted M-solutions to certain BSVIEs.     

Path regularity for solutions of backward stochastic differential equations

 In this paper we study the path regularity of the adpated solutions to a class of backward stochastic differential equations (BSDE, for short) whose terminal values are allowed to be functionals of a forward diffusion. Using the new representation formula for the adapted solutions established in our previous work [7], we are able to show, under the mimimum Lipschitz conditions on the coefficients, that for a fairly large class of BSDEs whose terminal values are functionals that are either Lipschitz under the L ^∞ -norm or under the L ¹ -norm, then there exists a version of the adapted solution pair that has at least càdlàg paths. In particular, in the latter case the version can be chosen so that the paths are in fact continuous. Received: 26 May 2000 / Revised version: 1 December 2000 / Published online: 19 December 2001     

Backward stochastic Volterra integral equations and some related problems

Backward stochastic Volterra integral equations (BSVIEs, for short) are introduced. The existence and uniqueness of adapted solutions are established. A duality principle between linear BSVIEs and (forward) stochastic Volterra integral equations is obtained. As applications of the duality principle, a comparison theorem is proved for the adapted solutions of BSVIEs, and a Pontryagin type maximum principle is established for an optimal control of stochastic integral equations.     

Backward stochastic Volterra integral equations on Markov chains

This paper studies Backward Stochastic Volterra Integral Equations (BSVIEs) driven by finite state, continuous time Markov chains. First, the existence and uniqueness of the solutions to two types of BSVIEs are established. Second, some scalar and vector comparison theorems are given. Finally, the applications of BSVIEs to a linear-quadratic optimal control problem and time-inconsistent coherent risk measures are presented.     

Time regularity for stochastic Volterra equations by the dilation theorem

The dilation theorem of Nagy is applied to establish time regularity of the solutions to a class of stochastic evolutionary Volterra equations.     

Volterra integral equations

One presents a survey of the investigations in the theory of Volterra integral equations, reviewed in Ref. Zh. Mat. between 1966–1976.Translated from Itogi Nauki i Tekhniki, Matematicheskii Analiz, Vol. 15, pp. 131–198, 1977.     

New approach to optimal control of stochastic Volterra integral equations

ABSTRACT

We study optimal control of stochastic Volterra integral equations (SVIE) with jumps by using Hida-Malliavin calculus.

• We give conditions under which there exist unique solutions of such equations.

• Then we prove both a sufficient maximum principle (a verification theorem) and a necessary maximum principle via Hida-Malliavin calculus.

• As an application we solve a problem of optimal consumption from a cash flow modelled by an SVIE.

     

Singular Volterra integral equations

Existence results are presented for the singular Volterra integral equation y(t) = h(t) + ∫₀^t k(t, s) f(s, y(s)) ds, for t ∈ [0,T]. Here f may be singular at y = 0. As a consequence new results are presented for the n^th order singular initial value problem.     

Two-parameter stochastic Volterra equations

Mathematical Notes - We study two-parameter stochastic Volterra equations containing integrals over strong martingales and fields of bounded variation. For such equations, we prove the existence...     

Volterra integral equations and evolution equations with an integral condition

We suggest a simple method for reducing problems with an integral condition for evolution equations to a Volterra integral equation of the first kind. For Volterra equations of the convolution type, we indicate necessary and sufficient solvability conditions for the case in which the right-hand side lies in some classes of functions of finite smoothness. We use these conditions to construct examples of nonexistence of a local solution for the heat equation with an integral condition.     

Harmonic analysis of stochastic equations and backward stochastic differential equations

The BMO martingale theory is extensively used to study nonlinear multi-dimensional stochastic equations in ${\mathcal{R}^p}$ ( ${p\in [1,\infty)}$ ) and backward stochastic differential equations (BSDEs) in ${\mathcal{R}^p\times \mathcal{H}^p}$ ( ${p\in (1, \infty)}$ ) and in ${\mathcal{R}^\infty\times\overline{L^\infty}^{\rm BMO}}$ , with the coefficients being allowed to be unbounded. In particular, the probabilistic version of Fefferman’s inequality plays a crucial role in the development of our theory, which seems to be new. Several new results are consequently obtained. The particular multi-dimensional linear cases for stochastic differential equations (SDEs) and BSDEs are separately investigated, and the existence and uniqueness of a solution is connected to the property that the elementary solutions-matrix for the associated homogeneous SDE satisfies the reverse Hölder inequality for some suitable exponent p ≥ 1. Finally, some relations are established between Kazamaki’s quadratic critical exponent b(M) of a BMO martingale M and the spectral radius of the stochastic integral operator with respect to M, which lead to a characterization of Kazamaki’s quadratic critical exponent of BMO martingales being infinite.