Description
This course will be an introduction to stochastic analysis at the graduate level. The topics covered will include: (i) Continuous time Martingales; (ii) Brownian motion; (iii) Stochastic integration; (iv) Ito's lemma; (v) The Girsanov Theorem, and Novikov condition; (vi) Stochastic differential equations.
Prerequisite:
Probability (640:577 or equivalent)
Textbook:
I. Karatzas and S. E. Shreve: Brownian motion and stochastic calculus, Springer.