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From Statistics to Mathematical Finance

Festschrift in Honour of Winfried Stute
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117,69 €*

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Beschreibung:

This book, dedicated to Winfried Stute on the occasion of his 70th birthday, presents a unique collection of contributions by leading experts in statistics, stochastic processes, mathematical finance and insurance. The individual chapters cover a wide variety of topics ranging from nonparametric estimation, regression modelling and asymptotic bounds for estimators, to shot-noise processes in finance, option pricing and volatility modelling. The book also features review articles, e.g. on survival analysis.
Preface.- Review Chapters on Winfried Stute's Work, e.g. Stute's Work in Survival Analysis.- Novikov: Kolmogorov-Smirnov Statistics.- Albrecher: Insurance Mathematics.- Rüschendorf: Risk Bounds and Partial Dependence Information.- Schumacher: Kaplan-Meier Integrals.- Overbeck: Backward SDEs.- Häusler: On Empirical Distribution Functions Under Auxiliary Information.- Eichner: KARDE - An R package for Kernel-Adaptive Regression and Density Estimation.- Ferger: Asymptotic Tail Bounds for the Dempfle-Stute Estimator in General Regression Models.- Dikta: Semi-parametric Random Censorship Models.- Schmidt: Shot-Noise Processes in Finance.- Koul: Estimating the Error Distribution in a Single-index Model.- Zhu: A Review on Dimension Reduction-based Tests for Regressions.- Roussas: Limiting Experiments and Asymptotic Bounds on the Performance of Sequences of Estimators.- Bhattacharya: Nonparametric Stopping Rules for Detecting Small Changes in Location and Scale Families.- Cao: A Review on Bandwidth Selection for Density Estimation with Dependent Data.- de Uña: On Nonparametric Estimation from Truncated Samples.- Ferreira: Stochastic Processes Applied to Gender Gaps.- Delgado: On the Efficiency of Directional Model Checks for Regression.- Gonzalez-Manteiga: Goodness-of-fit Tests for Stochastic Volatility Models.- Eberlein: Option Pricing with Levy Processes.- Huskova: Change Point Detection with Multivariate Observations Based on Characteristic Functions.

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