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We prove existence and uniqueness of stochastic representations for solutions to elliptic and parabolic boundary value and obstacle problems associated with a degenerate Markov diffusion process. In particular, our article focuses on the…

Probability · Mathematics 2016-04-08 Paul M. N. Feehan , Camelia Pop

The purpose of this work is to explore the role that random arbitrage opportunities play in pricing financial derivatives. We use a non-equilibrium model to set up a stochastic portfolio, and for the random arbitrage return, we choose a…

Other Condensed Matter · Physics 2008-12-10 Sergei Fedotov , Stephanos Panayides

In this note, we derive the characteristic function expansion for logarithm of the underlying asset price in corrected Heston model as proposed by Fouque and Lorig.

Computational Finance · Quantitative Finance 2013-10-15 Ankush Agarwal

We develop at-the-money call-price and implied volatility asymptotic expansions in time to maturity for a class of asset-price models whose log returns follow a L\'evy process. Under mild assumptions placing the driving L\'evy process in…

Pricing of Securities · Quantitative Finance 2026-05-25 Allen Hoffmeyer , Christian Houdré

In this paper we study the asymptotic theory for quadratic variation of a harmonizable fractional $\al$-stable process. We show a law of large numbers with a non-ergodic limit and obtain weak convergence towards a L\'evy-driven Rosenblatt…

Probability · Mathematics 2023-02-28 Andreas Basse-O'Connor , Mark Podolskij

With $\bar{\partial}$-generalization of the Deift-Zhou steepest descent method, we investigate the long-time asymptotics of the solution to the Cauchy problem for the Hunter-Saxton (HS) equation \begin{eqnarray} &&u_{txx}-2\omega…

Analysis of PDEs · Mathematics 2023-12-15 Luman Ju , Kai Xu , Engui Fan

We derive a small-time expansion for out-of-the-money call options under an exponential Levy model, using the small-time expansion for the distribution function given in Figueroa-Lopez & Houdre (2009), combined with a change of num\'eraire…

Pricing of Securities · Quantitative Finance 2011-12-15 Jose E. Figueroa-Lopez , Martin Forde

A parsimonious generalization of the Heston model is proposed where the volatility-of-volatility is assumed to be stochastic. We follow the perturbation technique of Fouque et al (2011, CUP) to derive a first order approximation of the…

Pricing of Securities · Quantitative Finance 2017-06-06 Jean-Pierre Fouque , Yuri F. Saporito

In [1], we calibrated a one-factor Cheyette SLV model with a local volatility that is linear in the benchmark forward rate and an uncorrelated CIR stochastic variance to 3M caplets of various maturities. While caplet smiles for many…

Computational Finance · Quantitative Finance 2024-08-22 Arun Kumar Polala , Bernhard Hientzsch

An analytical formula for the probability distribution of stock-market returns, derived from the Heston model assuming a mean-reverting stochastic volatility, was recently proposed by Dragulescu and Yakovenko in Quantitative Finance 2002.…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Gilles Daniel

We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form of the stochastic term. We also discuss…

Statistical Finance · Quantitative Finance 2024-04-12 M. Dashti Moghaddam , Zhiyuan Liu , R. A. Serota

This article establishes an asymptotic theory for volatility estimation in an infinite-dimensional setting. We consider mild solutions of semilinear stochastic partial differential equations and derive a stable central limit theorem for the…

Statistics Theory · Mathematics 2023-03-14 Fred Espen Benth , Dennis Schroers , Almut E. D. Veraart

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

We study two complementary methodologies for calibrating implied volatility surfaces: analytical approximations and data-driven models based on rough path theory. On the analytical side, we revisit a second-order asymptotic expansion for…

Mathematical Finance · Quantitative Finance 2026-05-11 Elisa Alòs , Òscar Burés , Rafael de Santiago , Josep Vives

Recent empirical studies suggest that the volatilities associated with financial time series exhibit short-range correlations. This entails that the volatility process is very rough and its autocorrelation exhibits sharp decay at the…

Pricing of Securities · Quantitative Finance 2018-04-17 Josselin Garnier , Knut Solna

This study employs expected certainty equivalents to explore the reinsurance and investment issue pertaining to an insurer that aims to maximize the expected utility while being subject to random risk aversion. The insurer's surplus process…

Optimization and Control · Mathematics 2025-01-03 Jian-hao Kang , Zhun Gou , Nan-jing Huang

This investigation establishes a formal equivalence between the generalized Black-Scholes equation under a Quadratic Normal Volatility (QNV) specification and the stationary Schr\"odinger equation for a hyperbolic P\"oschl-Teller potential.…

Pricing of Securities · Quantitative Finance 2025-07-28 Joel Saucedo

In the first part of this thesis, we focus on American options in the Heston model. We first give an analytical characterization of the value function of an American option as the unique solution of the associated (degenerate) parabolic…

Probability · Mathematics 2019-11-13 Giulia Terenzi

Discrete fine-scale models, in the form of either particle or lattice models, have been formulated successfully to simulate the behavior of quasi-brittle materials whose mechanical behavior is inherently connected to fracture processes…

Materials Science · Physics 2016-02-17 Roozbeh Rezakhani , Gianluca Cusatis

We consider a regression framework where the design points are deterministic and the errors possibly non-i.i.d. and heavy-tailed (with a moment of order $p$ in $[1,2]$). Given a class of candidate regression functions, we propose a…

Statistics Theory · Mathematics 2025-06-03 Yannick Baraud , Guillaume Maillard
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