**Lectures on Stochastic Analysis**

by Thomas G. Kurtz

**Publisher**: University of Wisconsin 2007**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.

Download or read it online for free here:

**Download link**

(700KB, PDF)

## Similar books

**Lectures on Probability, Statistics and Econometrics**

by

**Marco Taboga**-

**statlect.com**

This e-book is organized as a website that provides access to a series of lectures on fundamentals of probability, statistics and econometrics, as well as to a number of exercises on the same topics. The level is intermediate.

(

**8051**views)

**Probability and Statistics for Geophysical Processes**

by

**D. Koutsoyiannis**-

**National Technical University of Athens**

Contents: The utility of probability; Basic concepts of probability; Elementary statistical concepts; Special concepts of probability theory in geophysical applications; Typical univariate statistical analysis in geophysical processes; etc.

(

**1326**views)

**Markov Chains and Mixing Times**

by

**D. A. Levin, Y. Peres, E. L. Wilmer**-

**American Mathematical Society**

An introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space.

(

**8586**views)

**CK-12 Basic Probability and Statistics: A Short Course**

by

**Brenda Meery**-

**CK-12.org**

CK-12 Foundation's Basic Probability and Statisticsâ€“ A Short Course is an introduction to theoretical probability and data organization. Students learn about events, conditions, random variables, and graphs and tables that allow them to manage data.

(

**14640**views)