Advanced Topics in Probability
by S.R.S. Varadhan
Publisher: New York University 2011
Number of pages: 203
Topics: Brownian Motion; Continuous Parameter Martingales; Diffusion Processes; Weak convergence and Compactness; Stochastic Integrals and Ito's formula; Markov Processes, Kolmogorov's equations; Stochastic Differential Equations; Existence and Uniqueness; Girsanov Formula; Random Time Change; The two dimensional case; The General Case; Limit Theorems; Reflected Brownian Motion; Reflection in higher dimensions; Invariant Measures.
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by Edward Nelson - Princeton University Press
In this book Nelson develops a new approach to probability theory that is just as powerful as but much simpler than conventional Kolmogorov-style probability theory used throughout mathematics for most of the 20th century.
by Remco van der Hofstad - Eindhoven University of Technology
These lecture notes are intended to be used for master courses, where the students have a limited prior knowledge of special topics in probability. We have included many of the preliminaries, such as convergence of random variables, etc.
by David Nualart - The University of Kansas
From the table of contents: Stochastic Processes (Probability Spaces and Random Variables, Definitions and Examples); Jump Processes (The Poisson Process, Superposition of Poisson Processes); Markov Chains; Martingales; Stochastic Calculus.
by Patrick Roger - BookBoon
The book is intended to be a technical support for students in finance. Topics: Probability spaces and random variables; Moments of a random variable; Usual probability distributions in financial models; Conditional expectations and Limit theorems.