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We develop a new model selection method for the adaptive robust efficient nonparametric signal estimation observed with impulse noise which is defined by the general non Gaussian L\'evy processes. On the basis of the developed method, we…

Statistics Theory · Mathematics 2018-11-27 Slim Beltaief , Oleg Chernoyarov , Serguei Pergamenchtchikov

We derive an explicit asymptotic approximation for implied volatilities of caplets under the assumption that the short-rate is described by a generic quadratic term-structure model. In addition to providing an asymptotic accuracy result, we…

Mathematical Finance · Quantitative Finance 2022-12-09 Matthew Lorig , Natchanon Suaysom

We consider the least-square linear regression problem with regularization by the l1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptotic analysis of model consistency of the Lasso. For various…

Machine Learning · Computer Science 2008-12-18 Francis Bach

The fundamental model of a periodic structure is a periodic point set up to rigid motion or isometry. Our recent paper in SoCG 2021 defined isometry invariants (density functions), which are complete in general position and continuous under…

Materials Science · Physics 2021-05-12 Daniel Widdowson , Marco Mosca , Angeles Pulido , Vitaliy Kurlin , Andrew I Cooper

We study multidimensional stochastic volatility models in which the volatility process is a positive continuous function of a continuous multidimensional Volterra process that can be not self-similar. The main results obtained in this paper…

Probability · Mathematics 2022-09-15 Giulia Catalini , Barbara Pacchiarotti

This Ph.D. thesis explores approximations and regularity for the Heston stochastic volatility model through three interconnected works. The first work focuses on developing high-order weak approximations for the Cox-Ingersoll-Ross (CIR)…

Numerical Analysis · Mathematics 2025-05-01 Edoardo Lombardo

Non-asymptotic theory of random matrices strives to investigate the spectral properties of random matrices, which are valid with high probability for matrices of a large fixed size. Results obtained in this framework find their applications…

Probability · Mathematics 2013-08-02 Mark Rudelson

We propose a generic calibration framework to both vanilla and no-touch options for a large class of continuous semi-martingale models. The method builds upon the forward partial integro-differential equation (PIDE) derived in Hambly et al.…

Mathematical Finance · Quantitative Finance 2025-11-19 Alan Bain , Matthieu Mariapragassam , Christoph Reisinger

In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead…

Mathematical Finance · Quantitative Finance 2017-02-17 Jean-Pierre Fouque , Ning Ning

We construct asymptotic expansions of Laplace type for the time-dependent quantum averages for Bose systems with many degrees of freedom, initially populated in coherent states. These solutions are localized in phase space, and they are…

Quantum Physics · Physics 2009-11-07 Misha Vishik , Gennady Berman

The quadratic rough Heston model provides a natural way to encode Zumbach effect in the rough volatility paradigm. We apply multi-factor approximation and use deep learning methods to build an efficient calibration procedure for this model.…

Computational Finance · Quantitative Finance 2022-05-31 Mathieu Rosenbaum , Jianfei Zhang

We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. (2021) with the pointwise two-stage calibration of Bayer et al. (2018) and Liu et al.…

Pricing of Securities · Quantitative Finance 2024-01-15 Fabio Baschetti , Giacomo Bormetti , Pietro Rossi

In this paper we extend our recent work on two-dimensional (2D) diffusive search-and-capture processes with multiple small targets (narrow capture problems) by considering an asymptotic expansion of the Laplace transformed probability flux…

Statistical Mechanics · Physics 2021-04-28 Paul C Bressloff

The local volatility model is a widely used for pricing and hedging financial derivatives. While its main appeal is its capability of reproducing any given surface of observed option prices---it provides a perfect fit---the essential…

Computational Finance · Quantitative Finance 2019-01-24 Martin Tegnér , Stephen Roberts

We consider the moderate deviations behaviors for two (co-) volatility estima-tors: generalised bipower variation, Hayashi-Yoshida estimator. The results are obtained by using a new result about the moderate deviations principle for…

Probability · Mathematics 2017-02-06 Hacène Djellout , Arnaud Guillin , Hui Jiang , Yacouba Samoura

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process…

Pricing of Securities · Quantitative Finance 2009-06-03 A. Gulisashvili , E. M. Stein

The calibration of a local volatility models to a given set of option prices is a classical problem of mathematical finance. It was considered in multiple papers where various solutions were proposed. In this paper an extension of the…

Computational Finance · Quantitative Finance 2016-08-19 Andrey Itkin , Alexander Lipton

In this paper, we obtain asymptotic formulas with error estimates for the implied volatility associated with a European call pricing function. We show that these formulas imply Lee's moment formulas for the implied volatility and the…

Pricing of Securities · Quantitative Finance 2009-06-03 A. Gulisashvili

We prove a large deviations principle for the class of multidimensional affine stochastic volatility models considered in (Gourieroux, C. and Sufana, R., J. Bus. Econ. Stat., 28(3), 2010), where the volatility matrix is modelled by a…

Pricing of Securities · Quantitative Finance 2018-06-20 Aurélien Alfonsi , David Krief , Peter Tankov

Selected recent contributions involving fluctuating velocity fields to the rapidly developing domain of stochastic field theory are reviewed. Functional representations for solutions of stochastic differential equations and master equations…

Statistical Mechanics · Physics 2016-11-22 Michal Hnatič , Juha Honkonen , Tomáš Lučivjanský