Unit STOCHASTIC DIFFERENTIAL EQUATIONS

Course
Mathematics
Study-unit Code
A005439
Curriculum
Matematica per analisi di sistemi complessi e dati
Teacher
Irene Benedetti
Teachers
  • Irene Benedetti
Hours
  • 42 ore - Irene Benedetti
CFU
6
Course Regulation
Coorte 2025
Offered
2025/26
Learning activities
Caratterizzante
Area
Formazione matematica teorica avanzata
Academic discipline
MAT/05
Type of study-unit
Opzionale (Optional)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
Italian
Contents
Stationary Processes, Martingales, Gaussian Processes. Brownian Motion and elements of Stochastic Calculus: Riemann-Stiljes integral, Ito integral, Ito process, stochastic differential equations.
Reference texts
Grimmett-Stirzaker: Probability and Random Processes; Clarendon Press, Oxford (1982). A. Pascucci, PDE and Martingale Methods in Option Pricing, Bocconi University Press, Springer 2011
Educational objectives
Generally, after passing the exam, the student has a deep knowledge of the general properties of the main stochastic processes, and skillness in the methods of studying and connecting them, together with some ability in stochastic calculus. The students particularly motivated could be invited to face also some first-level research problems.
Prerequisites
Some basic notions of Elementary Probability and Measure Theory should be already known to the students.
Teaching methods
Lectures in classroom
Other information
Student office: https://www.unipg.it/personale/irene.benedetti/didattica visit the webpage: www.unistudium.unipg.it For info on support services for students with Specific Learning Disorders and/or Disabilities please refer to the web page: http://www.unipg.it/disabilita-e-dsa
Learning verification modality
Oral exam: the test usually lasts about 40 minutes. The student should give definitions, theorems and proofs contained in the program as well as solve some very simple exercises. The aim of the colloquium is to evaluate if and to what extent the student is acquainted with the main topics studied, and check his/her capability in handling them, establishing connections and consequences. For info on support services for students with Specific Learning Disorders and/or Disabilities please refer to the web page: http://www.unipg.it/disabilita-e-dsa
Extended program
Martingales: general properties, convergence theorems, characterization in L_2. Optional theorem and Wald Formula. Gaussian processes: general theory, examples, Wiener process and its properties. Brownian Motion: existence and approximation, properties if its trajectories, scale invariance, Iterated Logarithm Theorem and the Arcsin Law. Stochastic Integration: Stieltjes and Ito integrals. Ito formulas and stochastic differentials. Stochastic differential equations: existence and uniqueness theorem, methods of solution in the linear case.
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