Quantitative Analysis
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I. Basic math.
1. Conditional probability.
2. Normal distribution.
3. Brownian motion.
4. Poisson process.
5. Ito integral.
6. Ito calculus.
7. Change of measure.
8. Girsanov's theorem.
9. Forward Kolmogorov's equation.
10. Backward Kolmogorov's equation.
11. Optimal control, Bellman equation, Dynamic programming.
A. Deterministic optimal control problem.
B. Stochastic optimal control problem.
C. Optimal stopping time problem. Free boundary problem.
II. Pricing and Hedging.
III. Explicit techniques.
IV. Data Analysis.
V. Implementation tools.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Optimal control, Bellman equation, Dynamic programming.


e will be using techniques developed in the section ( Backward Kolmogorov equation ) to attach PDE formulations to problems of optimal control in stochastic situation.




A. Deterministic optimal control problem.
B. Stochastic optimal control problem.
C. Optimal stopping time problem. Free boundary problem.

Notation. Index. Contents.


















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