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Given a L\'evy process $L$, we consider the so-called statistical Skorohod embedding problem of recovering the distribution of an independent random time $T$ based on i.i.d. sample from $L_{T}.$ Our approach is based on the genuine use of…

Statistics Theory · Mathematics 2014-07-04 Denis Belomestny , John Schoenmakers

The goal of this paper is to investigate the tools of extreme value theory originally introduced for discrete time stationary stochastic processes (time series), namely the tail process and the tail measure, in the framework of continuous…

Probability · Mathematics 2021-03-31 Philippe Soulier

Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of options in a fast mean-reverting stochastic volatility setting. Four examples are provided in…

Pricing of Securities · Quantitative Finance 2012-05-15 Jean-Pierre Fouque , Sebastian Jaimungal , Matthew Lorig

Stochastic volatility models describe asset prices $S_t$ as driven by an unobserved process capturing the random dynamics of volatility $\sigma_t$. Here, we quantify how much information about $\sigma_t$ can be inferred from asset prices…

Statistical Finance · Quantitative Finance 2015-12-29 Nils Bertschinger , Oliver Pfante

In this paper, we study a kind of constrained backward stochastic differential equations (BSDEs) such that the nonlinear expectation of the composition of a loss function and the solution remains above zero. The existence and uniqueness…

Probability · Mathematics 2025-11-24 Hanwu Li

A reflection map, induced by the deterministic Skorohod problem on the nonnegative orthant, is applied to an $\mathbb{R}^n$ valued function $X$ on $[0,\infty)$ and then to $a+X$, where $a$ is a nonnegative constant vector. A question that…

Probability · Mathematics 2012-10-09 Offer Kella , Sundareswaran Ramasubramanian

We propose a new financial model, the stochastic volatility model with sticky drawdown and drawup processes (SVSDU model), which enables us to capture the features of winning and losing streaks that are common across financial markets but…

Mathematical Finance · Quantitative Finance 2025-03-20 Yuhao Liu , Pingping Jiang , Gongqiu Zhang

This paper provides convergence analysis for the approximation of a class of path-dependent functionals underlying a continuous stochastic process. In the first part, given a sequence of weak convergent processes, we provide a sufficient…

Probability · Mathematics 2013-07-22 Qingshuo Song , George Yin , Qing Zhang

In uncertainty quantification, critical parameters of mathematical models are substituted by random variables. We consider dynamical systems composed of ordinary differential equations. The unknown solution is expanded into an orthogonal…

Numerical Analysis · Mathematics 2019-04-10 Roland Pulch , Florian Augustin

This paper shows how to recover a stochastic volatility model (SVM) from a market model of the VIX futures term structure. Market models have more flexibility for fitting of curves than do SVMs, and therefore are better suited for pricing…

Pricing of Securities · Quantitative Finance 2022-03-16 Andrew Papanicolaou

In this paper, we study a collection of mean-reflected backward stochastic differential equations driven by $G$-Brownian motions ($G$-BSDEs), where $G$-expectations are constrained in some time-dependent intervals. To establish…

Probability · Mathematics 2024-07-26 Zihao Gu , Hui Zhao

We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. The credit losses are integrated into a structural model of default events…

Risk Management · Quantitative Finance 2015-03-20 Simone Farinelli , Mykhaylo Shkolnikov

We consider the fluctuations of generalized currents in stochastic Markovian dynamics. The large deviations of current fluctuations are shown to obey a Gallavotti-Cohen (GC) type symmetry in systems with a finite state space. However, this…

Statistical Mechanics · Physics 2008-06-06 A. Rákos , R. J. Harris

We consider stochastic control systems affected by a fast mean reverting volatility $Y(t)$ driven by a pure jump L\'evy process. Motivated by a large literature on financial models, we assume that $Y(t)$ evolves at a faster time scale…

Probability · Mathematics 2014-05-27 Martino Bardi , Annalisa Cesaroni , Andrea Scotti

We address stability of a class of Markovian discrete-time stochastic hybrid systems. This class of systems is characterized by the state-space of the system being partitioned into a safe or target set and its exterior, and the dynamics of…

Optimization and Control · Mathematics 2011-03-09 Debasish Chatterjee , Soumik Pal

We present a stochastic volatility market model where volatility is correlated with return and is represented by an Ornstein-Uhlenbeck process. With this model we exactly measure the leverage effect and other stylized facts, such as mean…

Condensed Matter · Physics 2007-05-23 Josep Perello , Jaume Masoliver

Financial studies require volatility based models which provides useful insights on risks related to investments. Stochastic volatility models are one of the most popular approaches to model volatility in such studies. The asset returns…

Methodology · Statistics 2021-10-26 Soham Mukherjee

We consider a general N-degree-of-freedom dissipative system which admits of chaotic behaviour. Based on a Fokker-Planck description associated with the dynamics we establish that the drift and the diffusion coefficients can be related…

Chaotic Dynamics · Physics 2009-10-31 Bidhan Chandra Bag , Deb Shankar Ray

We investigate a generalized stochastic model with the property known as mean reversion, that is, the tendency to relax towards a historical reference level. Besides this property, the dynamics is driven by multiplicative and additive…

Physics and Society · Physics 2009-11-11 C. Anteneodo , R. Riera

In this paper, we investigate a class of mean reflected McKean-Vlasov stochastic differential equation, which extends the equation proposed by \cite{briand2020particles} by allowing the solution's distribution to not only constrain its…

Probability · Mathematics 2024-11-21 Shaopeng Hong , Sheng Xiao