ESMA 6789 Stochastic Processes

General Syllabus
Homeworks and Exams
Probability Basics of Probability Theory
Random Variables and Random Vectors
Expectation of R.V.'s
Some Standard Random Variables
Functions of a R.V. - Transformations
Inequalities and Limit Theorems
Stochastic Processes Introduction
Poisson Process and Renewal Theory Poisson Process
Generalizations of the Poisson Process
Renewal Theory
Markov Chains and Markov Processes Discrete - time Markov Chains
Examples of Discrete-time Markov Chains
Continuous-time Markov Chains
Other Stochastic Processes Martingales
Brownian Motion
Stochastic Differential Equations
Stationary Processes and Ergodic Theory
Simulation and R Introduction to R
A list of useful R commands
Generating Random Variables Basic Methods and The Accept-Reject Algorithm
MCMC - Markov Chain Monte Carlo