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In this article we study the asymptotic behaviour of the realized quadratic variation of a process $\int_{0}^{t}u_{s}dY_{s}^{(1)}$% , where $u$ is a $\beta$-H\"older continuous process with $\beta > 1-H$ and…

Probability · Mathematics 2018-02-28 Salwa Bajja , Khalifa Es-Sebaiy , Lauri Viitasaari

Motivated by empirical evidence from the joint behavior of realized volatility time series, we propose to model the joint dynamics of log-volatilities using a multivariate fractional Ornstein-Uhlenbeck process. This model is a multivariate…

Statistical Finance · Quantitative Finance 2026-05-19 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

We consider the asymptotic behavior of the fluctuations for the empirical measures of interacting particle systems with singular kernels. We prove that the sequence of fluctuation processes converges in distribution to a generalized…

Probability · Mathematics 2024-12-31 Zhenfu Wang , Xianliang Zhao , Rongchan Zhu

The paper is devoted to three-parametric self-similar Gaussian Volterra processes that generalize fractional Brownian motion. We study the asymptotic growth of such processes and the properties of long- and short-range dependence. Then we…

Statistics Theory · Mathematics 2023-02-08 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

In this paper, we consider the statistical inference of the drift parameter $\theta$ of non-ergodic Ornstein-Uhlenbeck~(O-U) process driven by a general Gaussian process $(G_t)_{t\ge 0}$. When $H \in (0, \frac 12) \cup (\frac 12,1) $ the…

Statistics Theory · Mathematics 2022-07-28 Yanping Lu

We consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Lo\`{e}ve expansion for the…

Mathematical Finance · Quantitative Finance 2017-02-08 Archil Gulisashvili , Frederi Viens , Xin Zhang

In the present paper we study the asymptotic behavior of the auto-covariance function for Ornstein-Uhlenbeck (OU) processes driven by Gaussian noises with stationary and non-stationary increments and for Hermite OU processes. Our results…

Probability · Mathematics 2022-01-19 Khalifa Es-Sebaiy

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic…

Statistics Theory · Mathematics 2020-01-22 Jean-Marc Azaïs , François Bachoc , Agnès Lagnoux , Thi Mong Ngoc Nguyen

We study the strong approximation of a rough volatility model, in which the log-volatility is given by a fractional Ornstein-Uhlenbeck process with Hurst parameter $H<1/2$. Our methods are based on an equidistant discretization of the…

Probability · Mathematics 2016-06-14 Andreas Neuenkirch , Taras Shalaiko

Using multiple stochastic integrals and the Malliavin calculus, we analyze the asymptotic behavior of quadratic variations for a specific non-Gaussian self-similar process, the Rosenblatt process. We apply our results to the design of…

Probability · Mathematics 2009-12-21 Ciprian Tudor , Frederi Viens

We study the asymptotic behaviour of modified weighted power variations of the Hermite process of arbitrary order. By selecting suitable "good" increments and exploiting their decomposition into dominant independent components, we establish…

Statistics Theory · Mathematics 2026-01-06 Antoine Ayache , laurent Loosveldt , Ciprian Tudor

We consider a positive stationary generalized Ornstein--Uhlenbeck process \[V_t=\mathrm{e}^{-\xi_t}\biggl(\int_0^t\mathrm{e}^{\xi_{s-}}\ ,\mathrm{d}\eta_s+V_0\biggr)\qquadfor t\geq0,\] and the increments of the integrated generalized…

Statistics Theory · Mathematics 2010-02-24 Vicky Fasen

Starting from the notion of multivariate fractional Brownian Motion introduced in [F. Lavancier, A. Philippe, and D. Surgailis. Covariance function of vector self-similar processes. Statistics & Probability Letters, 2009] we define a…

Probability · Mathematics 2025-09-16 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

\noindent \textbf{Abstract}: We consider the parameter estimation problem for the Ornstein-Uhlenbeck process $X$ driven by a fractional Ornstein-Uhlenbeck process $V$, i.e. the pair of processes defined by the non-Markovian continuous-time…

Probability · Mathematics 2016-10-14 Brahim El Onsy , Khalifa Es-Sebaiy , Frederi G. Viens

In this paper, we investigate the parameter estimation for threshold Ornstein$\mathit{-}$Uhlenbeck processes. Least squares method is used to obtain continuous-type and discrete-type estimators for the drift parameters based on continuous…

Statistics Theory · Mathematics 2024-03-28 Yuecai Han , Dingwen Zhang

We introduce time-inhomogeneous stochastic volatility models, in which the volatility is described by a nonnegative function of a Volterra type continuous Gaussian process that may have very rough sample paths. The main results obtained in…

Probability · Mathematics 2021-01-01 Archil Gulisashvili

For a class of stochastic models with Gaussian and rough mean-reverting volatility that embeds the genuine rough Stein-Stein model, we study the weak approximation rate when using a Euler type scheme with integrated kernels. Our first…

Probability · Mathematics 2026-02-23 Aurélien Alfonsi , Ahmed Kebaier

Motivated by the modeling of the temporal structure of the velocity field in a highly turbulent flow, we propose and study a linear stochastic differential equation that involves the ingredients of a Ornstein-Uhlenbeck process, supplemented…

Fluid Dynamics · Physics 2017-09-26 Laurent Chevillard

In this paper we study some convergence results concerning the one-dimensional distribution of a time-changed fractional Ornstein-Uhlenbeck process. In particular, we establish that, despite the time change, the process admits a Gaussian…

Probability · Mathematics 2020-11-06 Giacomo Ascione , Yuliya Mishura , Enrica Pirozzi

We compare systematically several classes of stochastic volatility models of stock market fluctuations. We show that the long-time return distribution is either Gaussian or develops a power-law tail, while the short-time return distribution…

Statistical Finance · Quantitative Finance 2010-09-15 Frantisek Slanina
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