Logo

Lectures on Stochastic Analysis

Lectures on Stochastic Analysis
by

Publisher: University of Wisconsin
Number of pages: 119

Description:
The course will introduce stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson random measures, stochastic differential equations for general Markov processes, change of measure, and applications to finance, filtering and control. The intention has been to state the theorems correctly with all hypotheses, but no attempt has been made to include detailed proofs.

Home page url

Download or read it online for free here:
Download link
(700KB, PDF)

Similar books

Book cover: A Minimum of Stochastics for ScientistsA Minimum of Stochastics for Scientists
by - Caltech
The book introduces students to the ideas and attitudes that underlie the statistical modeling of physical, chemical, biological systems. The text contains material the author have tried to convey to an audience composed mostly of graduate students.
(13587 views)
Book cover: Bayesian Spectrum Analysis and Parameter EstimationBayesian Spectrum Analysis and Parameter Estimation
by - Springer
This work is a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis.
(19584 views)
Book cover: Introduction to Probability Theory and Statistics for LinguisticsIntroduction to Probability Theory and Statistics for Linguistics
by - UCLA
Contents: Basic Probability Theory (Conditional Probability, Random Variables, Limit Theorems); Elements of Statistics (Estimators, Tests, Distributions, Correlation and Covariance, Linear Regression, Markov Chains); Probabilistic Linguistics.
(14878 views)
Book cover: Probability, Statistics and Stochastic ProcessesProbability, Statistics and Stochastic Processes
by
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).
(13610 views)