Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
Services
Author
Printable PDF file
I.
Basic math.
1.
Conditional probability.
A.
Definition of conditional probability.
B.
A bomb on a plane.
C.
Dealing a pair in the "hold' em" poker.
D.
Monty-Hall problem.
E.
Two headed coin drawn from a bin of fair coins.
F.
Randomly unfair coin.
G.
Recursive Bayesian calculation.
H.
Birthday problem.
I.
Backward induction.
J.
Conditional expectation. Filtration. Flow of information. Stopping time.
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.
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.
Conditional probability.
onditional probability is a tool for updating conjectured view of the world using increasing amount of gradually incoming information. We provide definition, main properties and consider several examples of calculation.
A.
Definition of conditional probability.
B.
A bomb on a plane.
C.
Dealing a pair in the "hold' em" poker.
D.
Monty-Hall problem.
E.
Two headed coin drawn from a bin of fair coins.
F.
Randomly unfair coin.
G.
Recursive Bayesian calculation.
H.
Birthday problem.
I.
Backward induction.
J.
Conditional expectation. Filtration. Flow of information. Stopping time.
Notation.
Index.
Contents.
Copyright 2007