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Fractional Brownian motion has become a standard tool to address long-range dependence in financial time series. However, a constant memory parameter is too restrictive to address different market conditions. Here we model the price…

Mathematical Finance · Quantitative Finance 2024-07-31 Axel A. Araneda

We analyze the effect of additive fractional noise with Hurst parameter $H > \frac{1}{2}$ on fast-slow systems. Our strategy is based on sample paths estimates, similar to the approach by Berglund and Gentz in the Brownian motion case. Yet,…

Probability · Mathematics 2020-02-19 Katharina Eichinger , Christian Kuehn , Alexandra Neamtu

The Black-Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time-to-maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power…

Mathematical Finance · Quantitative Finance 2015-01-29 Masaaki Fukasawa

We investigate a system of Brownian particles weakly bound by attractive parity-symmetric potentials that grow at large distances as $V(x) \sim |x|^\alpha$, with $0 < \alpha < 1$. The probability density function $P(x,t)$ at long times…

Statistical Mechanics · Physics 2024-07-24 Lucianno Defaveri , Eli Barkai , David A. Kessler

We consider a microstructure foundation for rough volatility models driven by Poisson random measures. In our model the volatility is driven by self-exciting arrivals of market orders as well as self-exciting arrivals of limit orders and…

Probability · Mathematics 2024-12-24 Ulrich Horst , Wei Xu , Rouyi Zhang

The convergence of the first order Euler scheme and an approximative variant thereof, along with convergence rates, are established for rough differential equations driven by c\`adl\`ag paths satisfying a suitable criterion, namely the…

Probability · Mathematics 2025-09-16 Andrew L. Allan , Anna P. Kwossek , Chong Liu , David J. Prömel

In this paper we provide sufficient conditions for sequences of stochastic processes of the form $\int_{[0,t]} f_n(u) \theta_n(u) du$, to weakly converge, in the space of continuous functions over a closed interval, to integrals with…

Probability · Mathematics 2025-04-02 Xavier Bardina , Salim Boukfal

In this work we study fractal properties of rough differential equations driven by a fractional Brownian motions with Hurst parameter $H>\frac{1}{4}$. In particular, we show that the Hausdorff dimension of the sample paths of the solution…

Probability · Mathematics 2015-01-29 Shuwen Lou , Cheng Ouyang

We present a fast and robust calibration method for stochastic volatility models that admit Fourier-analytic transform-based pricing via characteristic functions. The design is structure-preserving: we keep the original pricing transform…

Computational Finance · Quantitative Finance 2025-10-23 Keyuan Wu , Tenghan Zhong , Yuxuan Ouyang

This paper is devoted to study a class of stochastic Volterra equations associated with fractional Brownian motion. We first prove the Driver type integration by parts formula and the shift Harnack type inequalities. As a direct…

Probability · Mathematics 2014-07-24 XiLiang Fan

Uncertainties are abundant in complex systems. Mathematical models for these systems thus contain random effects or noises. The models are often in the form of stochastic differential equations, with some parameters to be determined by…

Numerical Analysis · Mathematics 2015-03-13 Jiarui Yang , Jinqiao Duan

We prove the existence of weak solutions for distribution-dependent stochastic Volterra equations under linear growth and continuity conditions on the coefficients and mild regularity assumptions on the kernels, including singular kernels.…

Probability · Mathematics 2026-04-28 Martin Bergerhausen , David J. Prömel

We study the approximation of stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H>1/2$. For the mean-square error at a single point we derive the optimal rate of convergence that can be achieved…

Probability · Mathematics 2007-06-19 Andreas Neuenkirch

In this paper we derive a efficient Monte Carlo approximation for the price of path-dependent derivatives under the multiscale stochastic volatility models of Fouque \textit{et al}. Using the formulation of this pricing problem under the…

Computational Finance · Quantitative Finance 2020-05-12 Yuri F. Saporito

We estimate the Hurst parameter $H \in (0,1)$ of a fractional Brownian motion from discrete noisy data, observed along a high frequency sampling scheme. When the intensity $\tau_n$ of the noise is smaller in order than $n^{-H}$ we establish…

Statistics Theory · Mathematics 2022-05-27 Grégoire Szymanski

In this paper, we investigate reflected backward stochastic differential equations driven by rough paths (rough RBSDEs), which can be viewed as probabilistic representations of nonlinear rough partial differential equations (rough PDEs) or…

Probability · Mathematics 2025-01-07 Hanwu Li , Huilin Zhang , Kuan Zhang

Clifford analysis has been the field of active research for several decades resulting in various methods to solve problems in pure and applied mathematics. However, the area of stochastic analysis has not been addressed in its full…

Probability · Mathematics 2022-01-19 Swanhild Bernstein , Dmitrii Legatiuk

Motivated by a problematic coming from mathematical finance, this paper is devoted to existing and additional results of continuity and differentiability of the It\^o map associated to rough differential equations. These regularity results…

Probability · Mathematics 2019-01-16 Nicolas Marie

We present a new approach to noncommutative stochastic calculus that is, like the classical theory, based primarily on the martingale property. Using this approach, we introduce a general theory of stochastic integration and quadratic…

Operator Algebras · Mathematics 2025-10-28 David A. Jekel , Todd A. Kemp , Evangelos A. Nikitopoulos

We study approximations to a class of vector-valued equations of Burgers type driven by a multiplicative space-time white noise. A solution theory for this class of equations has been developed recently in [Hairer, Weber, Probab. Theory…

Probability · Mathematics 2016-06-02 Martin Hairer , Jan Maas , Hendrik Weber