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Related papers: Examples of It\^o c\`adl\`ag rough paths

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In the spirit of Marcus canonical stochastic differential equations, we study a similar notion of rough differential equations (RDEs), notably dropping the assumption of continuity prevalent in the rough path literature. A new metric is…

Probability · Mathematics 2019-02-12 Ilya Chevyrev , Peter K. Friz

We prove a rough It\^o formula for path-dependent functionals of $\alpha$-H\"older continuous paths for $\alpha\in(0,1)$. Our approach combines the sewing lemma and a Taylor approximation in terms of path-dependent derivatives.

Probability · Mathematics 2025-07-14 Franziska Bielert

Rough paths techniques give the ability to define solutions of stochastic differential equations driven by signals $X$ which are not semimartingales and whose $p$-variation is finite only for large values of $p$. In this context, rough…

Probability · Mathematics 2020-05-15 Yanghui Liu , Zachary Selk , Samy Tindel

The It\^o formula, also known as the change-of-variables formula, is a cornerstone of It\^o stochastic calculus. Over time, this formula has been extended to apply to random processes for which classical calculus is insufficient. Since…

Probability · Mathematics 2025-09-30 Nannan Li , Xing Gao

We consider rough paths with jumps. In particular, the analogue of Lyons' extension theorem and rough integration are established in a jump setting, offering a pathwise view on stochastic integration against cadlag processes. A class of…

Probability · Mathematics 2014-12-01 Peter Friz , Atul Shekhar

Solutions to linear controlled differential equations can be expressed in terms of iterated path integrals of the driving path. This collection of iterated integrals encodes essentially all information about the driving path. While upper…

Classical Analysis and ODEs · Mathematics 2019-05-29 Horatio Boedihardjo , Xi Geng , Nikolaos P. Souris

The purpose of this note is to prove the It{\^o}-F\"ollmer formula for the c\`adl\`ag paths possessing quadratic variation in a possibly ``weakest'' sense along some sequence of partitions. By this we mean, for example, that we do not…

Probability · Mathematics 2025-08-21 W. M. Bednorz , R. M. Łochowski , P. L. Zondi , F. J. Mhlanga , D. Hove

Based on an extension of the martingale comparison method some comparison results for path-dependent functions of semimartingales are established. The proof makes essential use of the functional It\^o calculus. A main tool is an extension…

Probability · Mathematics 2019-08-28 Benedikt Köpfer , Ludger Rüschendorf

New proofs are given of the existence of the compensator (or dual predictable projection) of a locally integrable c\'adl\'ag adapted process of finite variation and of the existence of the quadratic variation process for a c\'adl\'ag local…

Probability · Mathematics 2014-10-28 Alexander Sokol

We prove a universal approximation theorem that allows to approximate continuous functionals of c\`adl\`ag (rough) paths uniformly in time and on compact sets of paths via linear functionals of their time-extended signature. Our main…

Probability · Mathematics 2023-08-30 Christa Cuchiero , Francesca Primavera , Sara Svaluto-Ferro

In this article we study existence of pathwise stochastic integrals with respect to a general class of $n$-dimensional Gaussian processes and a wide class of adapted integrands. More precisely, we study integrands which are functions that…

Probability · Mathematics 2014-11-25 Zhe Chen , Lauri Viitasaari

We use simple sub-Riemannian techniques to prove that an arbitrary geometric p-rough path in the sense of Lyons (98) is the limit in sup-norm of a sequence of canonically lifted smooth paths, which are uniformly bounded in p-variation,…

Functional Analysis · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

The non-linear sewing lemma constructs flows of rough differential equations from a braod class of approximations called almost flows. We consider a class of almost flows that could be approximated by solutions of ordinary differential…

Classical Analysis and ODEs · Mathematics 2021-12-17 Antoine Lejay

We develop a variant of rough path theory tailor-made for analyzing a class of financial asset price models known as rough volatility models. As an application, we prove a pathwise large deviation principle (LDP) for a certain class of…

Probability · Mathematics 2023-12-27 Masaaki Fukasawa , Ryoji Takano

Extending It\^o's formula to non-smooth functions is important both in theory and applications. One of the fairly general extensions of the formula, known as Meyer-It\^o, applies to one dimensional semimartingales and convex functions.…

Mathematical Finance · Quantitative Finance 2015-07-02 Ramin Okhrati , Uwe Schmock

We show in this note how the machinery of C^1-approximate flows devised in the work "Flows driven by rough paths", and applied there to reprove and extend most of the results on Banach space-valued rough differential equations driven by a…

Probability · Mathematics 2013-09-25 Ismael Bailleul

Whenever an It\^o-Wentsel type of formula holds for composition of flows of a certain differential dynamics, there exists locally a decomposition of the corresponding flow according to complementary distributions (or foliations, in the case…

Probability · Mathematics 2022-12-20 Pedro Catuogno , Lourival Lima , Paulo Ruffino

The It{\^o} map assigns the solution of a Rough Differential Equation, a generalization of an Ordinary Differential Equation driven by an irregular path, when existence and uniqueness hold. By studying how a path is transformed through the…

Probability · Mathematics 2019-05-01 Laure Coutin , Antoine Lejay

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

We put forward a general framework for the study of a pathwise central limit theorem (CLT) and a moderate deviation principle (MDP) for stochastic partial differential equations perturbed with a small multiplicative linear noise by means of…

Probability · Mathematics 2023-07-21 Emanuela Gussetti