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In Liang et al (2009), the current authors demonstrated that BSDEs can be reformulated as functional differential equations, and as an application, they solved BSDEs on general filtered probability spaces. In this paper the authors continue…

Probability · Mathematics 2010-11-22 G. Liang , T. Lyons , Z. Qian

A system of dynamically consistent nonlinear evaluation (${\cal{F}}$-evaluation) provides an ideal characterization for the dynamical behaviors of risk measures and the pricing of contingent claims. The purpose of this paper is to study the…

Probability · Mathematics 2016-07-21 Shiqiu Zheng , Shoumei Li

This paper is devoted to proving a general invariant representation theorem for generators of general time interval backward stochastic differential equations, where the generator $g$ has a quadratic growth in the unknown variable $z$ and…

Probability · Mathematics 2021-11-12 Guangshuo Zhou , Fengjiao Du , Shengjun Fan

We study the forward investment performance process (FIPP) in an incomplete semimartingale market model with closed and convex portfolio constraints, when the investor's risk preferences are of the power form. We provide necessary and…

Probability · Mathematics 2022-01-27 Lijun Bo , Agostino Capponi , Chao Zhou

The purpose of this paper is to establish the well-posedness of martingale (probabilistic weak) solutions to stochastic degenerate aggregation--diffusion equations arising in biological and public health contexts. The studied equation is of…

Probability · Mathematics 2025-10-07 Mostafa Bendahmane , Mohamed Mehdaoui , Mouhcine Tilioua

We discuss martingales, detrending data, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). Beginning with x-independent drift coefficients R(t) we show that Martingale stochastic…

Physics and Society · Physics 2009-11-13 Joseph L. McCauley , Kevin E. Bassler , Gemunu H. Gunaratne

Let $X^1,\ldots, X^d$ be sigma-martingales on $(\Omega,{\cal F}, P)$. We show that every bounded martingale (with respect to the underlying filtration) admits an integral representation w.r.t. $X^1,\ldots, X^d$ if and only if there is no…

Probability · Mathematics 2015-12-15 Rajeeva L Karandikar , B V Rao

Let $\Phi = \{\phi_e\}_{e\in E}$ be a finitely irreducible conformal graph directed Markov system (CGDMS) with symbolic representation $E_A^{\infty}$ and limit set $J$. Under a mild condition on the system, we give a multifractal analysis…

Dynamical Systems · Mathematics 2025-02-04 Nathan Dalaklis

We investigate aspects of semimartingale decompositions, approximation and the martingale representation for multidimensional correlated Markov processes. A new interpretation of the dependence among processes is given using the martingale…

Statistics Theory · Mathematics 2015-02-24 Antonio Dalessandro , Gareth W. Peters

Let $Z^H= \{Z^H(t), t \in \R^N\}$ be a real-valued $N$-parameter harmonizable fractional stable sheet with index $H = (H_1, \ldots, H_N) \in (0, 1)^N$. We establish a random wavelet series expansion for $Z^H$ which is almost surely…

Probability · Mathematics 2019-03-12 Antoine Ayache , Narn-Rueih Shieh , Yimin Xiao

We analyse the structure of local martingale deflators projected on smaller filtrations. In a general continuous-path setting, we show that the local martingale part in the multiplicative Doob-Meyer decomposition of projected local…

Probability · Mathematics 2020-08-31 Constantinos Kardaras , Johannes Ruf

Herein, we analyze an efficient branching particle method for asymptotic solutions to a class of continuous-discrete filtering problems. Suppose that $t\to X_t$ is a Markov process and we wish to calculate the measure-valued process…

Probability · Mathematics 2007-05-23 Michael A. Kouritzin , Wei Sun

Lions and Musiela (2007) give sufficient conditions to verify when a stochastic exponential of a continuous local martingale is a martingale or a uniformly integrable martingale. Blei and Engelbert (2009) and Mijatovi\'c and Urusov (2012c)…

Probability · Mathematics 2014-07-10 Carole Bernard , Zhenyu Cui , Don McLeish

We formulate and solve the martingale problem in a nonlinear expectation space. Unlike the classical work of Stroock and Varadhan (1969) where the linear operator in the associated PDE is naturally defined from the corresponding diffusion…

Probability · Mathematics 2014-04-01 Xin Guo , Chen Pan , Shige Peng

In this paper we introduce a model, the stochastic fractional delay differential equation (SFDDE), which is based on the linear stochastic delay differential equation and produces stationary processes with hyperbolically decaying…

Probability · Mathematics 2018-06-21 Richard A. Davis , Mikkel Slot Nielsen , Victor Rohde

When the \textit{martingale representation property} holds, we call any local martingale which realizes the representation a \textit{representation process}. There are two properties of the \textit{representation process} which can greatly…

Probability · Mathematics 2016-03-18 Shiqi Song

In this paper, we investigate the Markovian iteration method for solving coupled forward-backward stochastic differential equations (FBSDEs) featuring a fully coupled forward drift, meaning the drift term explicitly depends on both the…

Numerical Analysis · Mathematics 2025-04-04 Zhipeng Huang , Cornelis W. Oosterlee

Let $\psi$ be a multi-dimensional random variable. We show that the set of probability measures $\mathbb{Q}$ such that the $\mathbb{Q}$-martingale $S^{\mathbb{Q}}_t=\mathbb{E}^{\mathbb{Q}}\left[\psi\lvert\mathcal{F}_{t}\right]$ has the…

Probability · Mathematics 2019-07-11 Dmitry Kramkov , Sergio Pulido

We propose a simple and original approach for solving linear-quadratic mean-field stochastic control problems. We study both finite-horizon and infinite-horizon pro\-blems, and allow notably some coefficients to be stochastic. Extension to…

Probability · Mathematics 2018-10-26 Matteo Basei , Huyên Pham

In this paper, we analyze the mean field backward stochastic differential equations (MFBSDEs) with double mean reflections, whose generator and constraints both depend on the distribution of the solution. When the generator is Lipschitz…

Probability · Mathematics 2026-01-12 Hanwu Li , Jin Shi