Stochastic flows of diffeomorphisms on an open set in rn

In this paper, we will give sufficient conditions for the solution to a stochastic differential equation (SDE) on an open set D in R" to define a stochastic flow of diffeomorphisms of D onto itself. Since a necessary and sufficient condition for the solution to determine a stochastic flow of diffeomorphisms is that the original SDE and its adjoint SDE are both strictly conservative, we will concentrate our attention on finding sufficient conditions for the SDE to be strictly conservative. It will be etablished that the strict conservativeness follows if the vector fields governing the SDE decay suitably near the boundary dD in the direction transversal to 3D and some additional assumptions are satisfied.     

隐Brown运动驱动的Poisson过程强度估计量的强相合性

针对金融、保险等领域研究中经常遇到的隐Brown运动驱动的Poisson过程模型,通过概率变换并利用鞅论方法等工具,证明了对模型中某些参数所提出的两类估计量的强相合性,用数值试验检验了它们的有效性.试验结果表明,文中所给两类估计方法均优于已有方法.     

非齐次马氏链的中心极限定理

本文将针对非齐次马氏链的转移矩阵列在Ces`aro收敛意义下,利用鞅的中心极限定理证明一个不同于Dobrushin结果的非齐次马氏链的中心极限定理。     

Risk Minimizing Option Pricing in a Regime Switching Market

Abstract

We study option pricing in a regime switching market where the risk free interest rate, growth rate and the volatility of a stock depends on a finite state Markov chain. Using a minimal martingale measure we show that the risk minimizing option price satisfies a system of Black–Scholes partial differential equations with weak coupling.     

Heterogeneous Spatial Dynamical Regression in a Hilbert-Valued Context

This article introduces a Hilbert-valued spatially dynamic regression model. The spatially heterogeneous functional trend is modeled by functional multiple regression, with varying regression operators. The spatial autoregressive Hilbertian model of order one (SARH(1) model, see [37 Ruiz-Medina , M.D. 2011 . Spatial autoregressive and moving average Hilbertian processes . J. Multivariate Anal. 102 : 292 – 305 .[Crossref] , [Google Scholar]]) is considered to represent the spatial correlation and dynamics displayed by the functional error term. The RKHS theory is applied in the construction of suitable bases for projection and regularization of the associated estimation problems. The performance of the proposed Hilbert-valued modeling and estimation methodology is illustrated with a real-data example, related to financing decisions from firm panel data.     

General Linear Quadratic Optimal Stochastic Control Problem Driven by a Brownian Motion and a Poisson Random Martingale Measure with Random Coefficients

In this article, we consider a linear-quadratic optimal control problem (LQ problem) for a controlled linear stochastic differential equation driven by a multidimensional Browinan motion and a Poisson random martingale measure in the general case, where the coefficients are allowed to be predictable processes or random matrices. By the duality technique, the dual characterization of the optimal control is derived by the optimality system (so-called stochastic Hamilton system), which turns out to be a linear fully coupled forward-backward stochastic differential equation with jumps. Using a decoupling technique, the connection between the stochastic Hamilton system and the associated Riccati equation is established. As a result, the state feedback representation is obtained for the optimal control. As the coefficients for the LQ problem are random, here, the associated Riccati equation is a highly nonlinear backward stochastic differential equation (BSDE) with jumps, where the generator depends on the unknown variables K, L, and H in a quadratic way (see (5.9) herein). For the case where the generator is bounded and is linearly dependent on the unknown martingale terms L and H, the existence and uniqueness of the solution for the associated Riccati equation are established by Bellman's principle of quasi-linearization.     

Φ′-VALUED MARTINGALE MEASURES AND THEIR LIMIT THEOREMS*

This work is devoted to the study of martingale measures with values in the dual of a nuclear space and to the construction of stochastic integrals with respect to some classes of these processes. This permits us to establish calculus and we introduce the concept of convergence of Φ′-valued martingale measures in distribution. The conditions are given for convergence of Φ′-valued martingale measures.