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This paper develops bootstrap methods to construct uniform confidence bands for nonparametric spectral estimation of L\'{e}vy densities under high-frequency observations. We assume that we observe $n$ discrete observations at frequency…

Statistics Theory · Mathematics 2017-05-30 Kengo Kato , Daisuke Kurisu

We construct nonparametric confidence sets for regression functions using wavelets that are uniform over Besov balls. We consider both thresholding and modulation estimators for the wavelet coefficients. The confidence set is obtained by…

Statistics Theory · Mathematics 2007-06-13 Christopher R. Genovese , Larry Wasserman

Financial markets based on L\'evy processes are typically incomplete and option prices depend on risk attitudes of individual agents. In this context, the notion of utility indifference price has gained popularity in the academic circles.…

Pricing of Securities · Quantitative Finance 2015-02-24 Clément Ménassé , Peter Tankov

We construct an estimator of the L\'evy density of a pure jump L\'evy process, possibly of infinite variation, from the discrete observation of one trajectory at high frequency. The novelty of our procedure is that we directly estimate the…

Probability · Mathematics 2020-04-06 Céline Duval , Ester Mariucci

Nonparametric methods for the estimation of the Levy density of a Levy process are developed. Estimators that can be written in terms of the ``jumps'' of the process are introduced, and so are discrete-data based approximations. A model…

Statistics Theory · Mathematics 2007-06-13 Enrique Figueroa-Lopez , Christian Houdre

In exponential semi-martingale setting for risky asset we estimate the difference of prices of options when initial physical measure $P$ and corresponding martingale measure $Q$ change to $\tilde{P}$ and $\tilde{Q}$ respectively. Then, we…

Probability · Mathematics 2018-03-14 L. Vostrikova

The accuracy of least squares calibration using option premiums and particle filtering of price data to find model parameters is determined. Derivative models using exponential L\'evy processes are calibrated using regularized weighted…

Pricing of Securities · Quantitative Finance 2017-05-16 Stavros J. Sioutis

Estimation methods for the L\'{e}vy density of a L\'{e}vy process are developed under mild qualitative assumptions. A classical model selection approach made up of two steps is studied. The first step consists in the selection of a good…

Statistics Theory · Mathematics 2016-08-16 José E. Figueroa-López , Christian Houdré

We investigate densities of vaguely continuous convolution semigroups of probability measures on $\mathbb{R}^d$. First, we provide results that give upper estimates in a situation when the corresponding jump measure is allowed to be highly…

Probability · Mathematics 2020-07-30 Tomasz Grzywny , Karol Szczypkowski

We consider a defaultable asset whose risk-neutral pricing dynamics are described by an exponential Levy-type martingale subject to default. This class of models allows for local volatility, local default intensity, and a locally dependent…

Probability · Mathematics 2013-12-30 Matthew Lorig , Stefano Pagliarani , Andrea Pascucci

For a converging sequence of exponential L\'evy models, we give conditions under which the associated sequence of option prices converges. We also study the behaviour of the prices when no such convergence holds. We then consider two…

Probability · Mathematics 2018-04-20 S. Cawston , L. Vostrikova

The accurate representation of epistemic uncertainty is a challenging yet essential task in machine learning. A widely used representation corresponds to convex sets of probabilistic predictors, also known as credal sets. One popular way of…

Machine Learning · Computer Science 2025-07-30 Mira Jürgens , Thomas Mortier , Eyke Hüllermeier , Viktor Bengs , Willem Waegeman

We propose a nonparametric parameter estimation of confidence intervals when the underlying has large or infinite variance. We explain the method by a simple numerical example and provide an application to estimate the coupling strength in…

Statistics Theory · Mathematics 2022-04-26 Anirban Das , Manfred Denker , Anna Levina , Lucia Tabacu

In this paper nonparametric methods to assess the multivariate L\'{e}vy measure are introduced. Starting from high-frequency observations of a L\'{e}vy process $\mathbf{X}$, we construct estimators for its tail integrals and the…

Statistics Theory · Mathematics 2013-08-14 Axel Bücher , Mathias Vetter

This article studies nonparametric methods to estimate the co-integrated volatility for multi-dimensional L\'evy processes with high frequency data. We construct a spectral estimator for the co-integrated volatility and prove minimax rates…

Statistics Theory · Mathematics 2019-09-24 Katerina Papagiannouli

This paper proposes a new method for estimating the joint probability mass function of a pair of discrete random variables. This estimator is used to construct joint Shannon R\'enyi-Tsallis entropies, and the mutual information estimates of…

Methodology · Statistics 2020-01-14 Amadou Diadie Ba , Gane Samb Lo , Cheikh Tidiane Seck

Generalizing the concept of quantiles to the jump measure of a L\'evy process, the generalized quantiles $q_{\tau}^{\pm}>0$, for $\tau>0$, are given by the smallest values such that a jump larger than $q_{\tau}^{+}$ or a negative jump…

Statistics Theory · Mathematics 2015-06-19 Mathias Trabs

We examine the small expiry behaviour of European call options in stock price models of exponential L\'evy type. In most cases of interest, we are able to identify the exact small expiry asymptotics. In "complete generality" we are able to…

Pricing of Securities · Quantitative Finance 2008-12-02 Michael Roper

We present an approach for pricing European call options in presence of proportional transaction costs, when the stock price follows a general exponential L\'{e}vy process. The model is a generalization of the celebrated work of Davis,…

Mathematical Finance · Quantitative Finance 2021-06-18 Nicola Cantarutti , João Guerra , Manuel Guerra , Maria do Rosário Grossinho

The paper considers so-called adaptive estimations of regression, distribution density and spectral density of a Gaussian stationary sequence, asymptotically optimal in order at a growing number of observation on any regular subspace…

Probability · Mathematics 2007-05-23 Eugene Ostrovsky , Leonid Sirota