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The classical Feynman-Kac formula states the connection between linear parabolic partial differential equations (PDEs), like the heat equation, and expectation of stochastic processes driven by Brownian motion. It gives then a method for…

Probability · Mathematics 2014-09-03 Huyen Pham

The challenge to fruitfully merge state-of-the-art techniques from mathematical finance and numerical analysis has inspired researchers to develop fast deterministic option pricing methods. As a result, highly efficient algorithms to…

Computational Finance · Quantitative Finance 2015-11-06 Kathrin Glau

A complex notion of backward stochastic differential equation (BSDE) is proposed in this paper to give a probabilistic interpretation for linear first order complex partial differential equation (PDE). By the uniqueness and existence of…

Probability · Mathematics 2015-05-15 Yuhong Xu

We study a class of backward doubly stochastic differential equations (BDSDEs) involving martingales with spatial parameters, and show that they provide probabilistic interpretations (Feynman-Kac formulae) for certain semilinear stochastic…

Probability · Mathematics 2017-12-05 Jian Song , Xiaoming Song , Qi Zhang

In this paper we show the existence and form uniqueness of a solution for multidimensional backward stochastic differential equations driven by a multidimensional L\'{e}vy process with moments of all orders. The results are important from a…

Probability · Mathematics 2012-02-01 Jianzhong Lin

Stochastic delay differential equations (SDDE's) have been used for financial modeling. In this article, we study a SDDE obtained by the equation of a CIR process, with an additional fixed delay term in drift; in particular, we prove that…

Probability · Mathematics 2018-06-05 Federico Flore , Giovanna Nappo

The Feynman-Kac formulae (FKF) express local solutions of partial differential equations (PDEs) as expectations with respect to some complementary stochastic differential equation (SDE). Repeatedly sampling paths from the complementary SDE…

Methodology · Statistics 2016-03-15 Jake Carson , Murray Pollock , Mark Girolami

We introduce a new class of anticipative backward stochastic differential equations with a dependence of McKean type on the law of the solution, that we name MKABSDE. We provide existence and uniqueness results in a general framework with…

Pricing of Securities · Quantitative Finance 2024-08-05 A. Agarwal , S. De Marco , E. Gobet , J. G. Lopez-Salas , F. Noubiagain , A. Zhou

In the framework of stochastic functional differential equations (SFDE's) and the corresponding calculus developed in the recent years by F. Yan and S. Mohammed, we provide a series of representation formulae for a variety of highly…

Probability · Mathematics 2016-02-29 Stefano Belloni

This paper studies how to price and hedge options under stock models given as a path-dependent SDE solution. When the path-dependent SDE coefficients have Fr\'{e}chet derivatives, an option price is differentiable with respect to time and…

Probability · Mathematics 2023-08-14 Kiseop Lee , Seongje Lim , Hyungbin Park

The paper is devoted to the construction of a probabilistic particle algorithm. This is related to nonlin-ear forward Feynman-Kac type equation, which represents the solution of a nonconservative semilinear parabolic Partial Differential…

Probability · Mathematics 2017-09-15 Anthony Le Cavil , Nadia Oudjane , Francesco Russo

We investigate the problem of pricing derivatives under a fractional stochastic volatility model. We obtain an approximate expression of the derivative price where the stochastic volatility can be composed of deterministic functions of time…

Pricing of Securities · Quantitative Finance 2022-10-28 Yuecai Han , Xudong Zheng

We study the pricing of derivative securities in financial markets modeled by a sub-mixed fractional Brownian motion with jumps (smfBm-J), a non-Markovian process that captures both long-range dependence and jump discontinuities. Under this…

Pricing of Securities · Quantitative Finance 2025-07-01 Nader Karimi

Although having been developed for more than two decades, the theory of forward backward stochastic differential equations is still far from complete. In this paper, we take one step back and investigate the formulation of FBSDEs. Motivated…

Probability · Mathematics 2017-12-27 Haiyang Wang , Jianfeng Zhang

In this paper we provide a generalization of a Feynmac-Kac formula under volatility uncertainty in presence of a linear term in the PDE due to discounting. We state our result under different hypothesis with respect to the derivation given…

Probability · Mathematics 2022-11-15 Bahar Akhtari , Francesca Biagini , Andrea Mazzon , Katharina Oberpriller

We present a computational alternative to probabilistic simulations for non-smooth stochastic dynamical systems that are prevalent in engineering mechanics. As examples, we target (1) stochastic elasto-plastic problems, which involve…

Probability · Mathematics 2019-05-23 Laurent Mertz , Georg Stadler , Jonathan Wylie

A representation formula for solutions of stochastic partial differential equations with Dirichlet boundary conditions is proved. The scope of our setting is wide enough to cover the general situation when the backward characteristics that…

Probability · Mathematics 2019-03-14 Máté Gerencsér , István Gyöngy

This paper presents a partial state of the art about the topic of representation of generalized Fokker-Planck Partial Differential Equations (PDEs) by solutions of McKean Feynman-Kac Equations (MFKEs) that generalize the notion of McKean…

Probability · Mathematics 2019-12-09 Lucas Izydorczyk , Nadia Oudjane , Francesco Russo

We propose an algorithm based on variational quantum imaginary time evolution for solving the Feynman-Kac partial differential equation resulting from a multidimensional system of stochastic differential equations. We utilize the…

In this paper, we introduce a type of path-dependent quasilinear (parabolic) partial differential equations in which the (continuous) paths on an interval [0,t] becomes the basic variables in the place of classical variables (t,x). This new…

Probability · Mathematics 2011-08-23 Shige Peng , Falei Wang
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