Introduction to Stochastic Analysis
by Michael Roeckner
Publisher: Universitaet Bielefeld 2011
Number of pages: 98
From the table of contents: Introduction to Pathwise Ito-Calculus; (Semi-)Martingales and Stochastic Integration; Markov Processes and Semigroups - Application to Brownian Motion; Girsanov Transformation; Time Transformation.
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by Marcel B. Finan - Arkansas Tech University
This manuscript will help students prepare for the Probability Exam, the examination administered by the Society of Actuaries. This examination tests a student's knowledge of the fundamental probability tools for quantitatively assessing risk.
by Oliver Knill - Overseas Press
This text covers material of a basic probability course, discrete stochastic processes including Martingale theory, continuous time stochastic processes like Brownian motion and stochastic differential equations, estimation theory, and more.
by John Venn - Macmillan And Company
No mathematical background is necessary for this classic of probability theory. It remains unsurpassed in its clarity, readability, and charm. It commences with physical foundations, examines logical superstructure, and explores various applications.
by Robert M. Gray - Springer
A self-contained treatment of the theory of probability, random processes. It is intended to lay theoretical foundations for measure and integration theory, and to develop the long term time average behavior of measurements made on random processes.