Poisson cluster measures: Quasi-invariance, integration by parts and equilibrium stochastic dynamics

The distribution μcl of a Poisson cluster process in X=Rd (with i.i.d. clusters) is studied via an auxiliary Poisson measure on the space of configurations in X=n_?Xn, with intensity measure defined as a convolution of the background intensity of cluster centres and the probability distribution of a generic cluster. We show that the measure μcl is quasi-invariant with respect to the group of compactly supported diffeomorphisms of X and prove an integration-by-parts formula for μcl. The corresponding equilibrium stochastic dynamics is then constructed using the method of Dirichlet forms.     

Linear systems and determinantal random point fields

In random matrix theory, determinantal random point fields describe the distribution of eigenvalues of self-adjoint matrices from the generalized unitary ensemble. This paper considers symmetric Hamiltonian systems and determines the properties of kernels and associated determinantal random point fields that arise from them; this extends work of Tracy and Widom. The inverse spectral problem for self-adjoint Hankel operators gives sufficient conditions for a self-adjoint operator to be the Hankel operator on L²(0,∞) from a linear system in continuous time; thus this paper expresses certain kernels as squares of Hankel operators. For suitable linear systems (−A,B,C) with one-dimensional input and output spaces, there exists a Hankel operator Γ with kernel ?(x)(s+t)=Ce−(2x+s+t)AB such that gx(z)=det(I+(z−1)ΓΓ†) is the generating function of a determinantal random point field on (0,∞). The inverse scattering transform for the Zakharov-Shabat system involves a Gelfand-Levitan integral equation such that the trace of the diagonal of the solution gives . When A?0 is a finite matrix and B=C†, there exists a determinantal random point field such that the largest point has a generalised logistic distribution.     

Applications of integration by parts formula for infinite-dimensional semimartingales

This work is devoted to the study of the behavior of stochastic evolution equations, obtained from stochastic flows, under the multiplicative transformations corresponding to the flows of Cameron-Martin transformations.     

An integration by parts formula in a Markovian regime switching model and application to sensitivity analysis

We establish an integration by parts formula for the random functionals of a continuous-time Markov chain, based on partial differentiation with respect to jump times. In comparison with existing methods, our approach does not rely on the Girsanov theorem and it imposes less restrictions on the choice of directions of differentiation, while assuming additional continuity conditions on the considered functionals. As an application we compute sensitivities (Greeks) using stochastic weights in an asset price model with Markovian regime switching.     

A numerically efficient closed-form representation of mean-variance hedging for exponential additive processes based on Malliavin calculus

ABSTRACT

We focus on mean-variance hedging problem for models whose asset price follows an exponential additive process. Some representations of mean-variance hedging strategies for jump-type models have already been suggested, but none is suited to develop numerical methods of the values of strategies for any given time up to the maturity. In this paper, we aim to derive a new explicit closed-form representation, which enables us to develop an efficient numerical method using the fast Fourier transforms. Note that our representation is described in terms of Malliavin derivatives. In addition, we illustrate numerical results for exponential Lévy models.     

Remarks on sub-fractional Bessel processes

Let S = {(St1,···,Std )}t≥0 denote a d-dimensional sub-fractional Brownian motion with index H ≥ 1/2. In this paper we study some properties of the process X of the formwhere Rt = ((St1)2+···+(Std)2)~1/2 is the sub-fractional Bessel process.     

Integration by parts on the Brownian Meander

We prove infinite-dimensional integration by parts formulae for the laws of the Brownian Meander, of the Bessel Bridge of dimension 3 between and of the Brownian Motion on the set of all paths taking values greater than or equal to a nonpositive constant. We give applications to SPDEs with reflection.

     

Concentration inequalities for stochastic differential equations of pure non-Poissonian jumps

We provide concentration inequalities for solutions to stochastic differential equations of pure not-necessarily Poissonian jumps. Our proofs are based on transportation cost inequalities for square integrable functionals of point processes with stochastic intensity and elements of stochastic calculus with respect to semi-martingales. We apply the general results to solutions of stochastic differential equations driven by renewal and non-linear Hawkes point processes.     

On the Upper Bound of the Density for Truncated Stable Processes in Small Time

We present a point-wise concrete upper bounds in a small time for transition densities of truncated stable process in R ^d, which have singular Lévy measures. We provide several examples.     

Malliavin calculus for Markov chains using perturbations of time

In this article, we develop a Malliavin calculus associated to a time-continuous Markov chain with finite state space. We apply it to get a criterion of density for solutions of stochastic differential equation involving the Markov chain and also to compute greeks.     

Stochastic Volterra equations driven by fractional Brownian motion

This paper is devoted to study a class of stochastic Volterra equations driven by fractional Brownian motion. We first prove the Driver type integration by parts formula and the shift Harnack type inequalities. As a direct application, we provide an alternative method to describe the regularities of the law of the solution. Secondly, by using the Malliavin calculus, the Bismut type derivative formula is established, which is then applied to the study of the gradient estimate and the strong Feller property. Finally, we establish the Talagrand type transportation cost inequalities for the law of the solution on the path space with respect to both the uniform metric and the L₂-metric.     

An integration by parts formula in submanifolds of positive codimension

We prove a general integration by parts formula for first‐order differential operators on submanifolds of arbitrary codimension of a given Riemannian manifold. The differential operators in question are assumed to satisfy a suitable tangentiality condition. Several particular cases, particularly relevant to applications to PDE arising in mathematical physics are discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

The quasi-invariance property for the Gamma kernel determinantal measure

The Gamma kernel is a projection kernel of the form (A(x)B(y)−B(x)A(y))/(x−y), where A and B are certain functions on the one-dimensional lattice expressed through Euler's Γ-function. The Gamma kernel depends on two continuous parameters; its principal minors serve as the correlation functions of a determinantal probability measure P defined on the space of infinite point configurations on the lattice. As was shown earlier [A. Borodin, G. Olshanski, Adv. Math. 194 (2005) 141–202, arXiv:math-ph/0305043], P describes the asymptotics of certain ensembles of random partitions in a limit regime.Theorem: The determinantal measure P is quasi-invariant with respect to finitary permutations of the nodes of the lattice.This result is motivated by an application to a model of infinite particle stochastic dynamics.     

高斯过程函数的中心极限定理与应用

采用Wiener空间的两个算子以及相关的恒等式,提出了新的方法证明了关于高斯过程函数的中心极限定理,并给出了该中心极限定理的应用实例.     

An initial-value method for the determinantal equations of vibrations and flutter

In many investigations in mechanics, we must solve the equation detB()=0, where the elements of the matrixB are general functions of . A method of solution is proposed, and results of numerical experiments are given.     

Integration by parts formulas concerning maxima of some SDEs with applications to study on density functions

In this article, we prove integration by parts (IBP) formulas concerning maxima of solutions to some stochastic differential equations (SDEs). We will deal with three types of maxima. First, we consider discrete time maximum, and then continuous time maximum in the case of one-dimensional SDEs. Finally, we deal with the maximum of the components of a solution to multi-dimensional SDEs. Applications to study their probability density functions by means of the IBP formulas are also discussed.