Probability for Finance

Ratings :
( 13 )
115 pages
This book provides technical support for students in finance.
This is a free eBook for students
Sign up for free access
Download free textbooks as PDF or read online. Less than 15% adverts
Free 30-day trial
Business subscription free for the first 30 days, then $5.99/mo
Latest eBooks
About the author

Patrick Roger is a professor of Finance at EM Strasbourg Business School, University of Strasbourg. He mainly teaches Derivatives, Investments, Behavioral Finance and taught Financial mathematics for more than 20 years at University Paris-Dauphine. As a member of LaRGE Research Center, he wrote more t...


This book provides technical support for students in finance. It reviews the main probabilistic tools used in financial models in a pedagogical way, starting from simple concepts like random variables and tribes and going to more sophisticated ones like conditional expectations and limit theorems. Many illustrations are given, taken from the financial literature. The book is also a prerequisite for “Stochastic Processes for Finance” published in the same collection.

  1. Probability spaces and random variables
    1. Measurable spaces and probability measures
    2. Conditional probability and Bayes theorem
    3. Random variables and probability distributions
  2. Moments of a random variable
    1. Mathematical expectation
    2. Variance and higher moments
    3. The vector space of random variables
    4. Equivalent probabilities and Radon-Nikodym derivatives
    5. Random vectors
  3. Usual probability distributions in financial models
    1. Discrete distributions
    2. Continuous distributions
    3. Some other useful distributions
  4. Conditional expectations and Limit theorems
    1. Conditional expectations
    2. Geometric interpretation in L2 (O, A, P)
    3. Properties of conditional expectations
    4. The law of large numbers and the central limit theorem
  5. Bibliography
Very well written with the right balance between concepts and applications. It is aptly named as probability for finance and is a very good primer for people who want to progress to advanced topics in mathematical finance. There were many gaps in my knowledge acquired during my masters in financial engineering and the author does a good job not only in explaining the concepts but also the need for these mathematical tools. Highly rated.
October 26, 2013 at 10:40 PM
More reviews