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Do you know about a good reference to understand Girsanov's Theorem? In particular, that explain why we need the assumptions of the theorem and what the theorem means in the practice?. I mean, an accurate probabilistic interpretation of $EX=1$ for dummies. I was reading the Kuo's book "Introduction to Stochastic Integration". I took a Stochastic Calculus course, but we only studied the construction of stochastic integral and some SDE. I'm really interested in this subject: This is the list of books that I've started to read:

1) Probability with Martingales - David Williams

2) Introduction to Stochastic Integration - Kuo

3) Stochastic Calculus and Applications - Samuel N. Cohen

4) Diffusion, Markov Processes and Martingales vol 1 and 2 - Rogers & Williams

Thank you!

Uriel Herrera
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    What assumptions of the theorem do you want to understand better? What do you mean by “in practice”? Its role and importance will vary depending on what field you’re using it in. (As will what constitutes a “good reference”) Try to ask a specific question or at least give more detail about where you’re coming from and what you don’t understand. – spaceisdarkgreen Jun 06 '18 at 18:00
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    A quick guide to understand the Girsanov theorem is to read page 164 of the book Stochastic Differential Equations by B. Oksendal. There are several helpful examples that use the Girsanov theorem (in a finance context - an application - as you asked for). – AXH Jun 22 '18 at 22:10
  • Arbitrage Theory in Continuous Time By Tomas Björk ? – BCLC Jul 31 '18 at 03:50

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