Joseph Najnudel
University of Zurich
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Publication
Featured researches published by Joseph Najnudel.
arXiv: Probability | 2009
Joseph Najnudel; Bernard Roynette; Marc Yor
The present volume is an expository monograph on Brownian penalisation, an important new notion the authors introduced to the theory of Wiener measure and Markov processes. It will serve as a concise guidebook for students and researchers who study probability theory, stochastic processes and mathematical finance.Published by Mathematical Society of Japan and distributed by World Scientific Publishing Co. for all markets
Duke Mathematical Journal | 2018
Reda Chhaibi; Thomas Madaule; Joseph Najnudel
In this paper, we investigate the extremal values of (the logarithm of) the characteristic polynomial of a random unitary matrix whose spectrum is distributed according the Circular Beta Ensemble (C
Publications of The Research Institute for Mathematical Sciences | 2011
Joseph Najnudel; Ashkan Nikeghbali
\beta
Annals of Applied Probability | 2013
C. P. Hughes; Joseph Najnudel; Ashkan Nikeghbali; Dirk Zeindler
E). More precisely, if
arXiv: Probability | 2010
Joseph Najnudel; Ashkan Nikeghbali
X_n
Journal of Statistical Physics | 2009
Joseph Najnudel; Ashkan Nikeghbali; Felix Rubin
is this characteristic polynomial and
arXiv: Probability | 2015
Joseph Najnudel
\mathbb{U}
arXiv: Probability | 2014
Joseph Najnudel; Ashkan Nikeghbali
the unit circle, we prove that:
Archive | 2014
Ismaël Bailleul; Lucian Beznea; Sergey Bocharov; Jean Brossard; Patrick Cattiaux; Iulian Cîmpean; Yinshan Chang; Koléhè A. Coulibaly-Pasquier; Michel Émery; Jacques Franchi; Xi Geng; Arnaud Guillin; Simon C. Harris; Andreas E. Kyprianou; Christian Léonard; Julien Letemplier; Christophe Leuridan; Carlo Marinelli; Joseph Najnudel; Ashkan Nikeghbali; J-L. Pérez; Vilmos Prokaj; Zhongmin Qian; Yan-Xia Ren; Michael Röckner; Mathieu Rosenbaum; Walter Schachermayer; Laurent Serlet; Thomas Simon; Dario Trevisan
Esaim: Probability and Statistics | 2011
Joseph Najnudel; Ashkan Nikeghbali
\sup_{z \in \mathbb{U} } \Re \log X_n(z) = \sqrt{\frac{2}{\beta}} \left(\log n - \frac{3}{4} \log \log n + \mathcal{O}(1) \right)\ ,