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Stochastic Processes for Finance

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104
Language:  English
This book is an extension of “Probability for Finance” to multi-period financial models, either in the discrete or continuous-time framework.
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This book is an extension of “Probability for Finance” to multi-period financial models, either in the discrete or continuous-time framework. It describes the most important stochastic processes used in finance in a pedagogical way, especially Markov chains, Brownian motion and martingales. It also shows how mathematical tools like filtrations, Itô’s lemma or Girsanov theorem should be understood in the framework of financial models. It also provides many illustrations coming from the financial literature.

  1. Discrete-time stochastic processes
    1. Introduction
    2. The general framework
    3. Information revelation over time
    4. Markov chains
    5. Martingales
  2. Continuous-time stochastic processes
    1. Introduction
    2. General framework
    3. The Brownian motion
  3. Stochastic integral and Itô’s lemma
    1. Introduction
    2. The stochastic integral
    3. Itô’s lemma
    4. The Girsanov theorem
    5. Stochastic differential equations
  4. Bibliography
  5. Index
Well-researched book
Very nice complement to probability for finance. Sufficiently developed to help for most problems and sufficiently simple to be understandable to students without a strong background in maths
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About the Author

Patrick Roger

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 than 15 books and 50 research papers in different areas of finance.