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Related papers: A regularity structure for rough volatility

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In this paper, we study the relationship between the short-end of the local and the implied volatility surfaces. Our results, based on Malliavin calculus techniques, recover the recent $\frac{1}{H+3/2}$ rule (where $H$ denotes the Hurst…

Mathematical Finance · Quantitative Finance 2023-09-18 Elisa Alòs , David García-Lorite , Makar Pravosud

Lyon's rough paths give an algebraic and analytic framework for Stieltjes integrals in a regime of low regularity where the usual Riemann-Stieltjes integral does not converge. Before we may rigorously define rough paths, we start with the…

Rings and Algebras · Mathematics 2021-12-10 Rosa Preiß

The recently developed rough Bergomi (rBergomi) model is a rough fractional stochastic volatility (RFSV) model which can generate more realistic term structure of at-the-money volatility skews compared with other RFSV models. However, its…

Mathematical Finance · Quantitative Finance 2021-09-21 Qinwen Zhu , Grégoire Loeper , Wen Chen , Nicolas Langrené

Stochastic Structural Stability Theory (SSST) provides an autonomous, deterministic, nonlinear dynamical system for evolving the statistical mean state of a turbulent system. In this work SSST is applied to the problem of understanding the…

Fluid Dynamics · Physics 2014-12-30 Brian F. Farrell , Petros J. Ioannou

In this article, we derive a Stratonovich and Skorohod type change of variables formula for a multidimensional Gaussian process with low H\"older regularity (typically lower than 1/4). To this aim, we combine tools from rough paths theory…

Probability · Mathematics 2013-08-05 Samy Tindel , Maria Jolis , Yaozhong Hu

Monitoring downside risk and upside risk to the key macroeconomic indicators is critical for effective policymaking aimed at maintaining economic stability. In this paper I propose a parametric framework for modelling and forecasting…

Econometrics · Economics 2023-11-21 Andrea Renzetti

Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the…

Methodology · Statistics 2015-12-18 Alexander Aue , Lajos Horvath , Daniel Pellatt

A new type of sectional curvature is introduced. The notion is purely algebraic and can be located in linear algebra as well as in differential geometry.

Differential Geometry · Mathematics 2015-04-07 Barbara Opozda

In previous works Avellaneda et al. pioneered the pricing and hedging of index options - products highly sensitive to implied volatility and correlation assumptions - with large deviations methods, assuming local volatility dynamics for all…

Pricing of Securities · Quantitative Finance 2022-12-16 Peter K. Friz , Thomas Wagenhofer

Spatial heteroskedasticity refers to stochastically changing variances and covariances in space. Such features have been observed in, for example, air pollution and vegetation data. We study how volatility modulated moving averages can…

Methodology · Statistics 2019-05-20 Michele Nguyen , Almut E. D. Veraart

The emergence of organized multiscale patterns resulting from convection is ubiquitous, observed throughout different cloud types. The reproduction of such patterns by general circulation models remains a challenge due to the complex nature…

Atmospheric and Oceanic Physics · Physics 2023-05-09 Mickael D. Chekroun , Tom Dror , Orit Altaratz , Ilan Koren

We construct a procedure for Bogoliubov-Parasiuk-Hepp-Zimmermann (BPHZ) renormalization of a rough path in view of the relation between rough path theory and regularity structure. We also provide a plain expression of the BPHZ-renormalized…

Probability · Mathematics 2021-03-15 Hayahide Ito

We develop the structure theory for transformations of weakly geometric rough paths of bounded $1 < p$-variation and their controlled paths. Our approach differs from existing approaches as it does not rely on smooth approximations. We…

Classical Analysis and ODEs · Mathematics 2022-09-01 Thomas Cass , Bruce K. Driver , Christian Litterer , Emilio Ferrucci

The inclusion of stochastic terms in equations of motion for fluid problems enables a statistical representation of processes which are left unresolved by numerical computation. Here, we derive stochastic equations for the behaviour of…

Fluid Dynamics · Physics 2023-03-22 Oliver D. Street

This article is the second one in a series on the use of scaling invariance in finance. In the first article (cond-mat/9906048), we introduced a new formalism for the pricing of derivative securities, which focusses on tradable objects…

Condensed Matter · Physics 2007-05-23 Jiri Hoogland , Dimitri Neumann

New classes of stochastic differential equations can now be studied using rough path theory (e.g. Lyons et al. [LCL07] or Friz--Hairer [FH14]). In this paper we investigate, from a numerical analysis point of view, stochastic differential…

Probability · Mathematics 2016-06-20 Christian Bayer , Peter K. Friz , Sebastian Riedel , John Schoenmakers

We extend the recently developed rough path theory for Volterra equations from (Harang and Tindel, 2019) to the case of more rough noise and/or more singular Volterra kernels. It was already observed in (Harang and Tindel, 2019) that the…

Probability · Mathematics 2021-02-23 Fabian A. Harang , Samy Tindel , Xiaohua Wang

A new class of fractional-order stochastic evolution equations of the form $(\partial_t + A)^\gamma X(t) = \dot{W}^Q(t)$, $t\in[0,T]$, $\gamma \in (0,\infty)$, is introduced, where $-A$ generates a $C_0$-semigroup on a separable Hilbert…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

We propose a new class of rough stochastic volatility models obtained by modulating the power-law kernel defining the fractional Brownian motion (fBm) by a logarithmic term, such that the kernel retains square integrability even in the…

Mathematical Finance · Quantitative Finance 2021-05-04 Christian Bayer , Fabian Andsem Harang , Paolo Pigato

We review opportunities for stochastic geometric mechanics to incorporate observed data into variational principles, in order to derive data-driven nonlinear dynamical models of effects on the variability of computationally resolvable…

Chaotic Dynamics · Physics 2018-06-28 François Gay-Balmaz , Darryl D. Holm