90480 - STOCHASTIC PROCESSES

Anno Accademico 2019/2020

  • Docente: Pietro Rigo
  • Crediti formativi: 6
  • SSD: SECS-S/01
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Statistical sciences (cod. 9222)

Conoscenze e abilità da conseguire

By the end of the course, the student knows the basic theory of stochastic processes and martingales. On the theoretical side, the student possesses the tools to prove the main results on existence and convergence of conditional expectations and martingales.

Contenuti

Review of a few basic concepts on probability theory

Conditional expectation

General notions about stochastic processes: Definition, paths, filtrations, stopping times, finite dimensional distributions

Existence of processes with given finite dimensional distributions (just an hint)

Martingales

Markov chains

Random walks

Brownian motion

Poisson process (consistently with the available time)


Testi/Bibliografia

Cinlar E. (2011) Probability and stochastic processes, Springer.

Grimmett G. and Stirzaker D. (2001) Probability and random processes, Oxford University Press.

Metodi didattici

Lectures and class exercises

Modalità di verifica e valutazione dell'apprendimento

Oral exam. During the exam, the student may be requested to discuss (not necessarily to solve) some simple exercises together with the teacher. Such exercises are obvious versions of exercises which have been solved in class

Strumenti a supporto della didattica

Notes and the text-books quoted above

Orario di ricevimento

Consulta il sito web di Pietro Rigo