Top Global Course Special Lectures by Prof. Víctor Rivero (Kyoto University / Centro de Investigación en Matemáticas) will take place as follows:
 Course Title
 Top Global Course Special Lectures 6
 Date & Time
 December 25 to 28, 2018 (8 lectures in 4 days)

 Tuesday, December 25, 13:1514:30 & 14:4516:00
 Wednesday, December 26, 13:1514:30 & 14:4516:00
 Thursday, December 27, 13:1514:30 & 14:4516:00
 Friday, December 28, 13:1514:30 & 14:4516:00
 Venue
 127 Conference room, Faculty of Science Bldg. #3, Kyoto University
 Title
 Fluctuation theory of Markov additive processes and selfsimilar Markov processes
 Abstract
 By a selfsimilar process we mean a stochastic process having the scaling property. Selfsimilar processes often arise in various parts of probability theory as limit of rescaled processes. Among several classes of selfsimilar processes, of particular interest to us is the class of selfsimilar strong Markov processes (ssMp).
 The ssMp's are involved for instance in branching processes, Lévy processes, coalescent processes and fragmentation theory. Some particularly wellknown examples are Brownian motion, Bessel processes, stable subordinators, stable processes, stable Lévy processes conditioned to stay positive, etc. Our main purpose in this course is to give a panorama of properties of ssMp's that have been obtained since the early sixties under the impulse of Lamperti's work, where the study of the case of positive valued ssMp's is initiated. The main result in Lamperti's work establishes that there is an explicit bijection between positive valued ssMp's and real valued Lévy processes. Recently it has been proved by Alili et al. that $\mathbb{R}^d$valued ssMp's are in a bijection with a generalization of Lévy processes, namely \emph{Markov Additive Processes} (MAP).
 In this course we will mainly focus in the study of ssMp's making a systematic application of the fluctuation theory of Lévy processes and MAP's. So, we will start by giving a review of some key results in the fluctuation theory of Lévy processes and random walks, and then extending some of those results to MAP's. We will study some particular examples, most of them are ssMp's obtained as a path transformation of stable processes.
 A detailed abstract is available at the following link:
https://www.math.kyotou.ac.jp/~kyano/files/20181225rivero_ktgu.pdf  Language
 English
 Note
 This series of lectures will be videorecorded and made available online.
Please note that anyone in the front rows of the room can be captured by a video camera.