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Related papers: Rough differential equations for volatility

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In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics on the Brownian motion that drives the volatility, one…

Mathematical Finance · Quantitative Finance 2025-03-24 Peter Bank , Christian Bayer , Peter K. Friz , Luca Pelizzari

In the setting of stochastic Volterra equations, and in particular rough volatility models, we show that conditional expectations are the unique classical solutions to path-dependent PDEs. The latter arise from the functional It\^o formula…

Probability · Mathematics 2026-05-27 Ofelia Bonesini , Antoine Jacquier , Alexandre Pannier

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process (not necessarily a semi-martingale). No adaptedness of initial point or vector fields is assumed. Under a simple condition on the…

Probability · Mathematics 2007-05-23 Laure Coutin , Peter Friz , Nicolas Victoir

We consider the problem of estimating the roughness of the volatility process in a stochastic volatility model that arises as a nonlinear function of fractional Brownian motion with drift. To this end, we introduce a new estimator that…

Statistical Finance · Quantitative Finance 2026-04-17 Xiyue Han , Alexander Schied

We analyze common lifts of stochastic processes to rough paths/rough drivers-valued processes and give sufficient conditions for the cocycle property to hold for these lifts. We show that random rough differential equations driven by such…

Probability · Mathematics 2016-12-07 Ismael Bailleul , Sebastian Riedel , Michael Scheutzow

We study solutions to backward differential equations that are driven hybridly by a deterministic discontinuous rough path $W$ of finite $q$-variation for $q \in [1, 2)$ and by Brownian motion $B$. To distinguish between integration of…

Probability · Mathematics 2025-05-28 Dirk Becherer , Yuchen Sun

This paper investigates the convergence of Wong--Zakai approximations to regime-switching stochastic differential equations, generated by a collection of finite-variation approximations to Brownian motion. We extend the results of Nguyen…

Probability · Mathematics 2023-04-21 Jasper Barr , Giang T. Nguyen , Oscar Peralta

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process lifted to a rough path. Neither adaptedness of initial point and vector fields nor commuting conditions between vector field is…

Probability · Mathematics 2011-11-10 Laure Coutin , Peter Friz , Nicolas Victoir

This paper develops an It\^o-type fractional pathwise integration theory for fractional Brownian motion with Hurst parameters \( H \in (\frac{1}{3}, \frac{1}{2}] \), using the Lyons' rough path framework. This approach is designed to fill…

Probability · Mathematics 2025-11-10 Zhongmin Qian , Xingcheng Xu

We construct a canonical geometric rough path over $d$-dimensional tempered fractional Brownian motion (tfBm) for any Hurst parameter $H > 1/4$ and tempering parameter $\lambda > 0$. The main challenge stems from the non-homogeneous nature…

Probability · Mathematics 2026-04-28 Atef Lechiheb

In quantitative finance, modeling the volatility structure of underlying assets is vital to pricing options. Rough stochastic volatility models, such as the rough Bergomi model [Bayer, Friz, Gatheral, Quantitative Finance 16(6), 887-904,…

Computational Finance · Quantitative Finance 2021-12-16 Christian Bayer , Eric Joseph Hall , Raúl Tempone

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 consider the rough differential equation $dY=f(Y)d\bm \om$ where $\bm \om=(\omega,\bbomega)$ is a rough path defined by a Brownian motion $\omega$ on $\RR^m$. Under the usual regularity assumption on $f$, namely $f\in C^3_b (\RR^d,…

Probability · Mathematics 2020-02-25 Hongjun Gao , María J. Garrido-Atienza , Anhui Gu , Kening Lu , Björn Schmalfuss

We consider the rough differential equations driven by tempered fractional Brownian motion with Hurst index $H\in (\frac{1}{4}, \frac{1}{3})$ and tempered parameter $\lambda>0$. First, by means of piecewise linear approximation, we…

Dynamical Systems · Mathematics 2026-03-10 Lijuan Zhang , Jianhua Huang

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

We prove a large deviation principle for the slow-fast rough differential equations under the controlled rough path framework. The driver rough paths are lifted from the mixed fractional Brownian motion with Hurst parameter $H\in…

Probability · Mathematics 2025-02-05 Xiaoyu Yang , Yong Xu

We give meaning to linear and semi-linear (possibly degenerate) parabolic partial differential equations with (affine) linear rough path noise and establish stability in a rough path metric. In the case of enhanced Brownian motion (Brownian…

Probability · Mathematics 2013-01-17 Peter Friz , Harald Oberhauser

We demonstrate two examples of stochastic processes whose lifts to geometric rough paths require a renormalisation procedure to obtain convergence in rough path topologies. Our first example involves a physical Brownian motion subject to a…

Probability · Mathematics 2018-12-14 Yvain Bruned , Ilya Chevyrev , Peter K. Friz

In this paper, we apply rough paths techniques to provide an approximation of the solution of stochastic functional differential equations driven by fractional Brownian motion with Hurst parameter $H>1/2$. Here, the involved stochastic…

Probability · Mathematics 2026-04-03 Johanna Garzón , Jorge A. León , Jorge Lozada , Soledad Torres

Rough volatility models are continuous time stochastic volatility models where the volatility process is driven by a fractional Brownian motion with the Hurst parameter smaller than half, and have attracted much attention since a seminal…

Statistics Theory · Mathematics 2019-05-20 Masaaki Fukasawa , Tetsuya Takabatake , Rebecca Westphal
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