正倒向随机微分方程解的比较定理

讨论了正倒向随机微分方程解的比较问题.阐述了正倒向随机微分方程在随机最优控制、现代金融理论中的广泛而深刻的应用, 对于一类正倒向随机微分方程, 利用Ito公式、停时等随机分析方法,通过构造辅助正倒向随机微分方程,得到了正倒向随机微分方程解的比较定理.     

关于随机微分方程Girsanov变奂的路径独立性

本文介绍了近十年来关于随机微分方程Girsanov变换的路径独立性的主要研究成果.该性质因反映了金融数学中市场的有效性而具有明确的应用背景,也因等价于一些非线性偏微分方程而具有数学研究价值.本文分别就经典的随机微分方程、带跳的随机微分方程、随机偏微分方程和分布依赖随机微分方程,介绍Girsanov变换的路径独立性所联系...     

随机脉冲随机微分方程解的存在唯一性

提出了随机脉冲随机微分方程模型,其中所谓的随机脉冲是指脉冲幅度由随机变量序列驱动,并且脉冲发生的时间也是一个随机变量序列.因此,随机脉冲随机微分方程是对带跳的随机微分方程模型的推广.利用Gronwall不等式、Lipschtiz条件和随机分析技巧,得到了随机脉冲随机微分方程的解的存在唯一性条件.     

基于超前倒向随机微分方程的动态风险度量

本文研究了基于超前倒向随机微分方程的时间相容的过程的动态凸(一致性)风险度量的问题.利用对超前倒向随机微分方程生成元的适当假设,建立超前倒向随机微分方程生成元与过程的动态凸(一致性)风险度量的对应模型,证明了超前倒向随机微分方程的解可以定义时间相容的过程的风险度量.得到了基于超前倒向随机微分方程的风险度量,推广了基于倒向随机微分方程的动态风险度量.由于超前倒向随机微分方程生成元中包含当前时刻和未来时刻的解,因此本文的结论对风险的预测更加可靠.     

随机游走和离散的倒向随机微分方程

本文研究了随机游走和离散的倒向随机微分方程。把随机游走到布朗运动的收敛推广到L^2情形；而且根据倒向随机微分方程的理论框架研究了离散的倒向随机微分方程，得到了离散的倒向随机微分方程解的存在唯一性和比较定理，这实际上给出了倒向随机微分方程的一种离散方法，为理论和实际研究提供了方便。     

非Lipschitz条件下半鞅随机微分方程解的唯一性(英文)

本文研究了非Lipschitz条件下半鞅随机微分方程.利用It(o)分析和Gronwall不等式,探讨了随机微分方程无爆炸解,并证明了随机微分方程解的唯一性.     

多维马尔科夫转制随机微分方程的数值解

由于多维马尔科夫转制随机微分方程不存在解析解,利用Euler—Maruyama方法给出多维马尔科夫转制随机微分方程的渐进数值解,并证明了此数值解收敛到方程的解析解．将单一马尔科夫转制随机微分方程的数值解问题延伸到多维马尔科夫转制情形,增强了马尔科夫转制随机微分方程的适用性．     

随机微分方程的无限时间跟踪

研究一类随机微分方程无限时间的跟踪性.首先给出了Ito型随机微分方程在均方意义下无限时间(ω,δ)-伪轨与无限时间(ω,ε)-跟踪的定义,其次证明了一个修正的Schauder不动点定理,最后用Malliavin导数证明了Ito随机微分方程的无限时间跟踪的存在性定理.推广确定的微分方程的跟踪性到随机情形,结论表明:在由Ito随机微分方程生成的随机动力系统中,依然存在无限时间的跟踪.     

利率均值回复模型下标的资产期权定价

在利率均值回复金融市场中 ,给出了财富贴现过程的随机微分方程 ;证明了与之联系的倒向随机微分方程解的存在唯一性 .最后 ,从倒向随机微分方程的解出发 ,得到了欧式期权定价的条件期望定价公式 .     

中立型随机比例微分方程的数值解的指数稳定性（英文）

本文主要利用半鞅收敛定理,研究中立型随机比例微分方程的数值稳定性.该文建立了线性的和非线性的中立型随机比例微分方程新的细则,我们将证明,在线性增长条件下,欧拉方法可以保留中立型随机比例微分方程的几乎处处指数稳定性,并且反向的欧拉方法能保留非线性的中立型随机比例微分方程的几乎处处指数稳定性.     

Parameter estimation for a price series model by solving a linear SDE with a Poisson component

A model of a series of price increments with jumps is constructed based on a linear stochastic differential equation with a Poisson component. Some estimates of unknown parameters of the model and SDE are obtained by using the method of moments. A statistical simulation algorithm for solving an SDE with a Poisson component in general form is proposed. Results of numerical experiments are given.     

一类线性混合模型的谱分解估计

谱分解估计(SDE)是新近提出的关于线性混合模型参数的一种新的估计方法,此方法的一个突出特点是同时给出固定效应参数和方差分量的显式解估计．本文就含两个方差分量的线性混合模型,对谱分解估计的性质做了进一步的研究,获得了方差分量的SDE和方差分析估计相等的充分必要条件,证明了在一定的条件下方差分量的SDE为一致最小方差无偏估计．     

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.     

A mean-reverting SDE on correlation matrices

We introduce a mean-reverting SDE whose solution is naturally defined on the space of correlation matrices. This SDE can be seen as an extension of the well-known Wright–Fisher diffusion. We provide conditions that ensure weak and strong uniqueness of the SDE, and describe its ergodic limit. We also shed light on a useful connection with Wishart processes that makes understand how we get the full SDE. Then, we focus on the simulation of this diffusion and present discretization schemes that achieve a second-order weak convergence. Last, we give a possible application of these processes in finance and argue that they could easily replace and improve the standard assumption of a constant correlation.     

Empirical analysis of self-adaptive differential evolution

Differential evolution (DE) is generally considered as a reliable, accurate, robust and fast optimization technique. DE has been successfully applied to solve a wide range of numerical optimization problems. However, the user is required to set the values of the control parameters of DE for each problem. Such parameter tuning is a time consuming task. In this paper, a self-adaptive DE (SDE) algorithm which eliminates the need for manual tuning of control parameters is empirically analyzed. The performance of SDE is investigated and compared with other well-known approaches. The experiments conducted show that SDE generally outperform other DE algorithms in all the benchmark functions. Moreover, the performance of SDE using the ring neighborhood topology is investigated.     

Analysis of estimation accuracy of the first moments of a Monte Carlo solution to an SDE with Wiener and Poisson components

In this paper, the estimation accuracy of the first moments of a numerical solution to an SDE with Wiener and Poisson components is investigated by a generalized explicit Euler method. Exact expressions for the mathematical expectation and variance of a test SDE solution are obtained. These expressions allow us to investigate the estimation accuracy obtained by a Monte Carlo method versus the SDE parameters, the integration step, and the size of the ensemble of simulated trajectories of the solution. The results of test numerical experiments are presented.     

Energy methods for stochastic differential equations

This article is devoted to the existence of strong solutions to stochastic differential equations (SDEs). Compared with Ito's theory, we relax the assumptions on the volatility term and replace the global Lipschitz continuity condition with a local Lipschitz continuity condition and a Hoelder continuity condition. In particular, our general SDE covers the Cox–Ingersoll–Ross SDE as a special case. We note that the general weak existence theory presumably extends to our general SDE (although the explicit time dependence of the drift term and the volatility term might require some extra considerations). However, avoiding weak existence theory we prove the existence of a strong solution directly using a priori estimates (the so-called energy estimates) derived from the SDE. The benefit of this approach is that the argument only requires some basic knowledge about stochastic and functional analysis. Moreover, the underlying principle has developed to become one of the cornerstones of the modern theory of partial differential equations (PDEs). In this sense, the general goal of this article is not just to establish the existence of a strong solution to the SDE under consideration but rather to introduce a new principle in the context of SDEs that has already proven to be successful in the context of PDEs.     

方差分量谱分解估计的几个性质

对于线性混合模型中方差分量的估计，虽有多种方法，但一般情况下只有方差分析估计和谱分解估计有显式解，本文就线性混合模型中含两个方差分量的情形，对方差分析估计和谱分解估计进行了比较，证明了在一些条件下两个估计的方差相等，由此推出谱分解估计也具有方差分析估计的某些优良性．文末用实例进一步说明了文中的结果．     

Stochastic processes adapted by neural networks with application to climate, energy, and finance

Local climate parameters may naturally effect the price of many commodities and their derivatives. Therefore we propose a joint framework for stochastic modeling of climate and commodity prices. In our setting, a stable Levy process is drift augmented to a generalized SDE. The related nonlinear function on the state space typically exhibits deterministic chaos. Additionally, a neural network adapts the parameters of the stable process such that the latter produces increasingly optimal differences between simulated output and observed data. Thus we propose a novel method of “intelligent” calibration of the stochastic process, using learning neural networks in order to dynamically adapt the parameters of the stochastic model.     

Une classification des flots solutions d'une EDS

Under general hypotheses, we show that the flows of kernels can be associated to a stochastic differential equation (SDE). We also show a classification theorem of the solutions of the SDE: they can be obtained through filtering the coalescing solution with respect to a sub-noise containing the white noise driving the SDE. The example of the isotropic flows is studied. To cite this article: Y. Le Jan, O. Raimond, C. R. Acad. Sci. Paris, Ser. I 336 (2003).