Masanori Hino, Kouhei Matsuura, Misaki Yonezawa
Here we study stochastic differential equations with a reflecting boundary condition. We provide sufficient conditions for pathwise uniqueness and non-explosion property of solutions in a framework admitting non-Lipschitz continuous coefficients and non-smooth domains.
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A Skorohod measurable universal functional representation of solutions to semimartingale SDEs
该研究证明了半鞅驱动的随机微分方程存在Skorohod可测泛函表示，即强解路径是驱动过程路径到带Skorohod拓扑的càdlàg函数空间的可测函数，可用于纯跳Lévy过程驱动SDE的Malliavin导数计算。
A new proof of pathwise uniqueness for SDEs with Sobolev diffusion and integrable drift term is introduced by extending a method from E. Fedrizzi and F. Flandoli (Pathwise uniqueness and continuous dependence of SDEs with non-regular drift, Stochastics 83 (2011), pp. 241--257) to the case of nonconstant diffusion.
We derive the optimal rate of convergence for the mean squared error at the terminal point for anticipating linear stochastic differential equations, where the integral is interpreted in Skorohod sense. Although alternative proof techniques are needed, our results can be seen as generalizations of the corresponding results for Itō SDEs. As a key tool we extend optimal approximation results for vectors of correlated Wiener integrals to general random vectors, which contain the solutions of our Skorohod SDEs.
In this paper we review and improve pathwise uniqueness results for some types of one-dimensional stochastic differential equations (SDE) involving the local time of the unknown process. The diffusion coefficient of the SDEs we consider is allowed to vanish on a set of positive measure and is not assumed to be smooth. As opposed to various existing results, our arguments are mainly based on the comparison theorem for local time and the occupation time formula. We apply our pathwise uniqueness results to derive strong existence and other properties of solutions for SDEs with rough coefficients.
For $α\in (0,1)$, we consider stochastic differential equations driven by one-sided stable processes of order $α$: \[dX_t= ϕ(X_{t-})\ dZ_t.\] We prove that pathwise uniqueness holds for this equation under the assumptions that $ϕ$ is continuous, non-decreasing and positive on $\R$. A counterexample is given to show that the positivity of $ϕ$ is crucial for pathwise uniqueness to hold.
A new proof of a pathwise uniqueness result of Krylov and Röckner is given. It concerns SDEs with drift having only certain integrability properties. In spite of the poor regularity of the drift, pathwise continuous dependence on initial conditions may be obtained, by means of this new proof. The proof is formulated in such a way to show that the only major tool is a good regularity theory for the heat equation forced by a function with the same regularity of the drift.
Our aim in this paper is to establish some strong stability properties of a solution of a stochastic differential equation driven by a fractional Brownian motion for which the pathwise uniqueness holds. The results are obtained using Skorokhod's selection theorem.
In this article, a class of second order differential equations on [0,1], driven by a general Hölder continuous function and with multiplicative noise, is considered. We first show how to solve this equation in a pathwise manner, thanks to Young integration techniques. We then study the differentiability of the solution with respect to the driving process and consider the case where the equation is driven by a fractional Brownian motion, with two aims in mind: show that the solution we have produced coincides with the one which would be obtained with Malliavin calculus tools, and prove that th…
Uniform pathwise stability of additive singular SDEs driven by fractional Brownian motion
本文研究了分数布朗运动驱动的加性奇异随机微分方程的长期行为，通过统一路径估计方法证明了解的均匀路径稳定性与不变测度的唯一性。
Strong solutions to degenerate SDEs and uniqueness for degenerate Fokker-Planck equations
本文通过受限Yamada-Watanabe定理，结合Fokker-Planck方程的存在性与新的受限路径唯一性结果，证明了退化SDE强解的存在性，并给出了Fokker-Planck方程的新唯一性结论。
Pathwise Convergence of a Modular Simulation Scheme for Hybrid SDEs with Memory
本文提出了一种具有记忆的混合随机微分方程(mH-SDEs)，扩展了传统混合随机微分方程模型，允许更丰富的依赖关系。开发了模块化-泊松算法，通过路径依赖均匀化生成离散跳跃，并利用现有SDE求解器进行欧几里得演化。理论贡献建立了路径收敛性并给出了显式速率，控制误差累积和过程解耦概率。
We study the well-posedness of a coupled system of Skorohod-like stochastic differential equations with reflecting boundary condition. The setting describes the evacuation dynamics of a mixed crowd composed of both active and passive pedestrians moving through a domain with obstacles, fire and smoke. As main working techniques, we use compactness methods and the Skorohod's representation of solutions to SDEs posed in bounded domains. This functional setting is a new point of view in the field of modeling and simulation pedestrian dynamics. The main challenge is to handle the coupling in the mo…
We present a new pathwise approximation scheme for stochastic differential equations driven by multidimensional Brownian motion which does not require the simulation of Lévy area and has a Wasserstein convergence rate better than the Euler scheme's strong error rate of $O(\sqrt{h})$, where $h$ is the step-size. By using rough path theory we avoid imposing any non-degenerate Hörmander or ellipticity assumptions on the vector fields of the SDE, in contrast to the similar papers of Alfonsi, Davie, and Malliavin et al. The scheme is based on the log-ODE method with the Lévy area increments replace…
Controlled rough SDEs, pathwise stochastic control and dynamic programming principles
本文研究粗糙随机微分方程的最优控制，建立路径动态规划原理与HJB稳定性，无需布朗统计，统一不同控制类别。
Sharp pathwise nonuniqueness for additive SDEs
研究通过构造速度场展示经典Zvonkin-Veretennikov-Davie强well-posedness在噪声 regime下的严格性，证明对于任意α<0，存在唯一弱解但不满足路径唯一性，从而无强解。
Weak Existence for Degenerate Distribution Dependent SDEs with multiplicative Noise -- a pathwise regularization approach
本研究将现有弱存在性技术拓展至分布依赖框架，结合路径平均与局部时分解方法，证明了带退化乘性噪声和奇异系数的分布依赖随机微分方程弱解的存在性，揭示了不规则噪声对随机系统退化相关分析难题的正则化作用。
We prove pathwise uniqueness for stochastic differential equations driven by non-degenerate symmetric $α$-stable Lévy processes with values in $\R^d$ having a bounded and $β$-Hölder continuous drift term. We assume $β> 1 - \fracα{2} $ and $α\in [ 1, 2)$. The proof requires analytic regularity results for associated integro-differential operators of Kolmogorov type. We also study differentiability of solutions with respect to initial conditions and the homeomorphism property.
We present a criterion for uniform in time convergence of the weak error of the Euler scheme for Stochastic Differential equations (SDEs). The criterion requires i) exponential decay in time of the space-derivatives of the semigroup associated with the SDE and ii) bounds on (some) moments of the Euler approximation. We show by means of examples (and counterexamples) how both i) and ii) are needed to obtain the desired result. If the weak error converges to zero uniformly in time, then convergence of ergodic averages follows as well. We also show that Lyapunov-type conditions are neither suffic…
Stability, uniqueness and existence of solutions to McKean-Vlasov SDEs: a multidimensional Yamada-Watanabe approach
该研究将Yamada-Watanabe假设推广至多维，在不构造Lyapunov函数的情况下，证明了带随机非Lipschitz系数的McKean-Vlasov SDE解的稳定性、唯一性及确定性情形下强解的存在性，还显式算出Lyapunov指数。
In this paper, we discuss exponential mixing property for Markovian semigroups generated by segment processes associated with several class of retarded Stochastic Differential Equations (SDEs) which cover SDEs with constant/variable/distributed time-lags. In particular, we investigate the exponential mixing property for (a) non-autonomous retarded SDEs by the Arzelà--Ascoli tightness characterization of the space $\C$ equipped with the uniform topology (b) neutral SDEs with continuous sample paths by a generalized Razumikhin-type argument and a stability-in-distribution approach and (c) jump-d…
For any real-valued stochastic process $X$ with cŕdlŕg paths we define non-empty family of processes which have locally finite total variation, have jumps of the same order as the process $X$ and uniformly approximate its paths on compacts. The application of the defined class is the definition of stochastic integral with semimartingale integrand and integrator as a limit of pathwise Lebesgue-Stieltjes integrals. This construction leads to the stochastic integral with some correction term (different from the Stratonovich integral). We compare the obtained result with classical results of Wong-…
Pathwise stability for one-dimensional SDEs driven by Brownian motion and a symmetric stable process
该研究针对由布朗运动和对称α-稳定过程驱动的一维SDE，通过同步耦合建立了定量逐路稳定性估计，明确了不同Hölder指数下的误差率，还得到了含可预测强迫误差和时间一致尾界的估计。
Stability, uniqueness and existence of solutions to McKean-Vlasov SDEs in arbitrary moments
该研究针对带随机/确定性系数的McKean-Vlasov随机微分方程，基于伊藤公式推导非利普希茨漂移下的解的存在唯一性、矩估计及带显式指数的稳定性，无需依赖李雅普诺夫函数。
Well-posedness and propagation of chaos for jump-type McKean-Vlasov SDEs with irregular coefficients
本文研究跳跃型McKean-Vlasov SDE在不规则系数下的强解适定性，并利用Yamada-Watanabe逼近和停时获得Euler格式的混沌传播与收敛速度。
Let (Y, Z) denote the solution to a forward-backward SDE. If one constructs a random walk B n from the underlying Brownian motion B by Skorohod embedding, one can show L 2 convergence of the corresponding solutions (Y n , Z n) to (Y, Z). We estimate the rate of convergence in dependence of smoothness properties, especially for a terminal condition function in C 2,$α$. The proof relies on an approximative representation of Z n and uses the concept of discretized Malliavin calculus. Moreover, we use growth and smoothness properties of the PDE associated to the FBSDE as well as of the finite diff…
Pathwise Iteration for Backward SDEs
本文提出一种新的数值方法，用于求解一类随机动态规划问题，这些问题源于反向随机微分方程或半线性偏微分方程的离散化。该方法通过迭代改进上界和下界来近似嵌套条件期望，适用于高维金融应用。
We study in this article the strong rate of convergence of the Euler-Maruyama scheme and associated with the jump-type equation introduced in Li and Mytnik. We obtain the strong rate of convergence under similar assumptions for strong existence and pathwise uniqueness. Models of this type can be considered as a generalization of the CIR (Cox-Ingersoll-Ross) process with jumps.
Strong Solutions to SDEs with Supercritical Drift Arising in Navigation Problems
针对极坐标下具有1/r型超临界奇异漂移的两种随机导航模型，通过路径论证证明了强存在性和路径唯一性，并研究了停止半径趋于零时的极限行为。
We pursue our investigations, initiated in [8], about stochastic integration with respect to the non-commutative fractional Brownian motion (NC-fBm). Our main objective in this paper is to compare the pathwise constructions of [8] with a Skorohod-type interpretation of the integral. As a first step, we provide details on the basic tools and properties associated with non-commutative Malliavin calculus, by mimicking the presentation of Nualart's celebrated treatise [14]. Then we check that, just as in the classical (commutative) situation, Skorohod integration can indeed be considered in the pr…
Killed path-dependent McKean-Vlasov SDEs for a probabilistic representation of non-conservative McKean PDEs
本文研究与正则化非保守路径依赖非线性抛物型McKean偏微分方程相关的带消亡路径依赖McKean-Vlasov SDE，证明强解的存在唯一性及次概率律正则性，其密度为PDE弱解，并讨论关联粒子系统适定性。
In this paper we obtain Gaussian-type lower bounds for the density of solutions to stochastic differential equations (SDEs) driven by a fractional Brownian motion with Hurst parameter $H$. In the one-dimensional case with additive noise, our study encompasses all parameters $H\in(0,1)$, while the multidimensional case is restricted to the case $H>1/2$. We rely on a mix of pathwise methods for stochastic differential equations and stochastic analysis tools.
Non-uniqueness for McKean--Vlasov SDEs with Hölder diffusion coefficients
该研究证明了具有Hölder扩散系数的一维McKean-Vlasov随机微分方程可能不满足唯一性，通过构造特定方程并结合扩散估计与Schauder不动点论证完成了相关结论的证明。
The paper focuses on discrete-type approximations of solutions to non-homogeneous stochastic differential equations (SDEs) involving fractional Brownian motion (fBm). We prove that the rate of convergence for Euler approximations of solutions of pathwise SDEs driven by fBm with Hurst index $H>1/2$ can be estimated by $O(δ^{2H-1})$ ($δ$ is the diameter of partition). For discrete-time approximations of Skorohod-type quasilinear equation driven by fBm we prove that the rate of convergence is $O(δ^H)$.
We prove pathwise uniqueness for a class of stochastic differential equations (SDE) on a Hilbert space with cylindrical Wiener noise, whose nonlinear drift parts are sums of the sub-differential of a convex function and a bounded part. This generalizes a classical result by one of the authors to infinite dimensions. Our results also generalize and improve recent results by N. Champagnat and P. E. Jabin, proved in finite dimensions, in the case where their diffusion matrix is constant and nondegenerate and their weakly differentiable drift is the (weak) gradient of a convex function. We also pr…
In this paper we introduce a new technique to construct unique strong solutions of SDEs with singular coefficients driven by certain Levy processes. Our method which is based on Malliavin calculus does not rely on a pathwise uniqueness argument. Furthermore, the approach, which provides a direct construction principle, grants the additional insight that the obtained solutions are Malliavin differentiable.
SDEs with subcritical Lebesgue--Hölder drift and driven by $α$-stable processes
本文研究由 α-稳定过程驱动且漂移处于次临界 Lebesgue–Hölder 空间的时间非齐次 SDE，建立弱适定性、强唯一性及 Davie 型唯一性，并以反例说明条件尖锐。
The present paper is devoted to the study of sample paths of G-Brownian motion and stochastic differential equations (SDEs) driven by G-Brownian motion from the view of rough path theory. As the starting point, we show that quasi-surely, sample paths of G-Brownian motion can be enhanced to the second level in a canonical way so that they become geometric rough paths of roughness 2 < p < 3. This result enables us to introduce the notion of rough differential equations (RDEs) driven by G-Brownian motion in the pathwise sense under the general framework of rough paths. Next we establish the funda…
Well-posedness of a system of SDEs driven by jump random measures
本文研究了具有非Lipschitz系数的SDE系统well-posedness，通过路径唯一性证明和比较定理，构建了非负可积解，并讨论了金融建模中的应用。
Pathwise Uniqueness for Multiplicative Young and Rough Differential Equations Driven by Fractional Brownian Motion
该研究证明了任意维度下由赫斯特参数$H\in(1/3,1)$的分数布朗运动驱动的乘性随机微分方程的轨道唯一性，通过结合随机平均估计与改进版随机缝合引理，放宽了波动率系数的赫尔德连续阶数要求，改进了已有经典结果。
Using elliptic and parabolic regularity results in $L^p$-spaces and generalized Dirichlet form theory, we construct for every starting point weak solutions to SDEs in $\mathbb{R}^d$ up to their explosion times including the following conditions. For arbitrary but fixed $p>d$ the diffusion coefficient $A=(a_{ij})_{1\le i,j\le d}$ is locally uniformly strictly elliptic with functions $a_{ij}\in H^{1,p}_{loc}(\mathbb{R}^d)$ and the drift coefficient $\mathbf{G}=(g_1,\dots, g_d)$ consists of functions $g_i\in L^p_{loc}(\mathbb{R}^d)$. The solution originates by construction from a Hunt process wit…
In the paper, we consider the no-explosion condition and pathwise uniqueness for SDEs driven by a Poisson random measure with coefficients that are super-linear and non-Lipschitz. We give a comparison theorem in the one-dimensional case under some additional condition. Moreover, we study the non-contact property and the continuity with respect to the space variable of the stochastic flow. As an application, we will show that there exists a unique strong solution for SDEs with coefficients like $x\log|x|$.
Consider the following stochastic differential equation (SDE) $$dX_t = b(t,X_{t-}) \, dt+ dL_t, \quad X_0 = x,$$ driven by a $d$-dimensional Lévy process $(L_t)_{t \geq 0}$. We establish conditions on the Lévy process and the drift coefficient $b$ such that the Euler--Maruyama approximation converges strongly to a solution of the SDE with an explicitly given rate. The convergence rate depends on the regularity of $b$ and the behaviour of the Lévy measure at the origin. As a by-product of the proof, we obtain that the SDE has a pathwise unique solution. Our result covers many important examples…
Quantitative approximation to density dependent SDEs driven by $α$-stable processes
本文基于中等相互作用粒子系统，利用 Duhamel 公式与鞅泛函不等式，为受 Brown 运动与 Lévy 过程驱动的密度依赖 McKean-Vlasov SDE 建立了定量逼近，推导出与噪声类型无关的精确经验测度收敛速率及弱与按轨道收敛速率。
The purpose of this paper is to study the existence and uniqueness of solutions to a system of Stochastic Differential Equations (SDEs). The coordinates are bounded by zero and one, and repulse each other according to a Coulombian like interaction force. We show the existence of strong and pathwise unique solutions to the system until the first multiple collision at zero or one, and give a sufficient condition on the parameters of the SDEs for this multiple collision not to occur in finite time.
In this paper we investigate two variants of $α$-stable processes, namely tempered stable subordinators and modified tempered stable process as well as their renormalization. We study the weak convergence in the Skorohod space and prove that they satisfy the uniform tightness condition. Finally, applications to the $α$-dependence of the solutions of SDEs driven by these processes are discussed.
We consider non-degenerate SDEs with a $β$-Holder continuous and bounded drift term and driven by a Levy noise $L$ which is of $α$-stable type. If $α\in [1,2)$ and $β\in (1 - \fracα{2},1) $ we show pathwise uniqueness and existence of a stochastic flow. We follow the approach of [Priola, Osaka J. Math. 2012] improving the assumptions on the noise $L$. In our previous paper $L$ was assumed to be non-degenerate, $α$-stable and symmetric. Here we can also recover relativistic and truncated stable processes and some classes of temperated stable processes.
Parameter dependent rough SDEs with applications to rough PDEs
本文研究参数依赖的粗糙 SDE 的 \mathscr{L}-可微性，用以建立粗糙 Kolmogorov 倒向方程正则解的适定性，并为去除相关随机滤波方程的维度依赖正则性假设奠定基础。
A BSDEs approach to pathwise uniqueness for stochastic evolution equations
本文利用无穷维正倒向随机微分方程系统，证明了一类Hilbert空间中漂移项为Hölder连续的随机发展方程的路径唯一性，并证明解对初值具有Lipschitz依赖性。
Pontryagin Maximum Principle for rough stochastic systems and pathwise stochastic control
本文提出了一种用于粗糙随机系统和路径随机控制问题的最大原理，证明了该问题与路径随机控制问题具有相同的价值函数，并展示了线性二次问题的最优控制结果。
We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a measurable way) on a finite number of sequential observations of the driving Brownian motion. The resulting lower error bounds hold in particular for all methods that are implementable on a computer and use a random number generator to simulate the driving Brownian motion at finitely many points. Our analysis shows that approximation at a single point is strongly con…
Sharp lower error bounds for strong approximation of SDEs with piecewise Lipschitz continuous drift coefficient
本文证明了在漂移系数分段Lipschitz连续且导数分段Lipschitz连续的标量SDE强逼近中，无需有界性和单调性假设即可达到最优$L^p$误差阶$3/4$，并利用此前仅用于上界的变换技术完成下界证明。
Stability-Optimized High Order Methods and Stiffness Detection for Pathwise Stiff Stochastic Differential Equations
本文提出四种方法处理路径刚性SDE，包括稳定性优化自适应方法、刚性估计器、L稳定隐式方法和自适应IMEX方法，显著提升求解效率，尤其在刚性化学反应网络中效率提升达8倍。
We study a class of self-similar jump type SDEs driven by Hölder-continuous drift and noise coefficients. Using the Lamperti transformation for positive self-similar Markov processes we obtain a necessary and sufficient condition for almost sure extinction in finite time. We then show that for certain parameters pathwise uniqueness holds in a restricted sense, namely among solutions spending a Lebesgue-negligible amount of time at 0. A direct power transformation plays a key role.
Motivated by the work of Musiela and Zariphopoulou \cite{zar-03}, we study the Itô random fields which are utility functions $U(t,x)$ for any $(ω,t)$. The main tool is the marginal utility $U_x(t,x)$ and its inverse expressed as the opposite of the derivative of the Fenchel conjuguate $\tU(t,y)$. Under regularity assumptions, we associate a $SDE(μ, σ)$ and its adjoint SPDE$(μ, σ)$ in divergence form whose $U_x(t,x)$ and its inverse $-\tU_y(t,y)$ are monotonic solutions. More generally, special attention is paid to rigorous justification of the dynamics of inverse flow of SDE. So that, we are a…
We consider the class of non-linear stochastic partial differential equations studied in \cite{conusdalang}. Equivalent formulations using integration with respect to a cylindrical Brownian motion and also the Skorohod integral are established. It is proved that the random field solution to these equations at any fixed point $(t,x)\in[0,T]\times \Rd$ is differentiable in the Malliavin sense. For this, an extension of the integration theory in \cite{conusdalang} to Hilbert space valued integrands is developed, and commutation formulae of the Malliavin derivative and stochastic and pathwise inte…
Random periodic solutions for stochastic differential equations with non-uniform dissipativity
本文研究非一致耗散随机微分方程随机周期解的存在性与唯一性，通过反射耦合和同步耦合方法，分别处理无记忆及有限/无限时滞情形，证明了分布意义与路径wise意义下的解的存在性。
Motivated by Girsanov's nonuniqueness examples for SDEs, we prove nonuniqueness for the parabolic stochastic partial differential equation (SPDE) \[\frac{\partial u}{\partial t}=\fracΔ{2}u(t,x) +\bigl|u(t,x)\bigr|^γ\dot{W}(t,x),\qquad u(0,x)=0.\] Here $\dot{W}$ is a space-time white noise on ${\mathbb {R}}_+\times {\mathbb {R}}$. More precisely, we show the above stochastic PDE has a nonzero solution for $0<γ<3/4$. Since $u(t,x)=0$ solves the equation, it follows that solutions are neither unique in law nor pathwise unique. An analogue of Yamada-Watanabe's famous theorem for SDEs was recently …
In this article, we present a general methodology for control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state processes controlled by mutually singular measures. The main result of this paper is the development of a concrete pathwise method for characterizing and computing near-optimal controls for abstract controlled Wiener functionals. The theory does not require ad hoc functional differentiability assumptions on the value process and elipticity conditions on the diffusion components. The analysis is pathwise over suitable finite dimensi…
Stochastic averaging for a class of stochastic differential equations (SDEs) with fractional Brownian motion, of the Hurst parameter H in the interval (1/2, 1), is investigated. An averaged SDE for the original SDE is proposed, and their solutions are quantitatively compared. It is shown that the solution of the averaged SDE converges to that of the original SDE in the sense of mean square and also in probability. It is further demonstrated that a similar averaging principle holds for SDEs under stochastic integral of pathwise backward and forward types. Two examples are presented and numerica…
We study the optimal control of path-dependent McKean-Vlasov equations valued in Hilbert spaces motivated by non Markovian mean-field models driven by stochastic PDEs. We first establish the well-posedness of the state equation, and then we prove the dynamic programming principle (DPP) in such a general framework. The crucial law invariance property of the value function V is rigorously obtained, which means that V can be viewed as a function on the Wasserstein space of probability measures on the set of continuous functions valued in Hilbert space. We then define a notion of pathwise measure …
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