Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
Services
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I. Basic math.
II. Pricing and Hedging.
III. Explicit techniques.
IV. Data Analysis.
V. Implementation tools.
1. Finite differences.
2. Gauss-Hermite Integration.
3. Asymptotic expansions.
4. Monte-Carlo.
A. Generation of random samples.
B. Acceleration of convergence.
a. Antithetic variables.
b. Control variate.
c. Importance sampling.
d. Stratified sampling.
C. Longstaff-Schwartz technique.
D. Calculation of sensitivities.
5. Convex Analysis.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Acceleration of convergence.


et $X,Y,Z$ be a random variables and MATH are random samples from $X,Y,Z$ . The letter $N$ usually denotes size of a sample. The notation $\sigma^{2}$ stands for standard deviation, $\mu$ is mean. The letters $a,b,c$ denote real numbers. The letters $f,g,h,p$ usually denote functions of real variable.




a. Antithetic variables.
b. Control variate.
c. Importance sampling.
d. Stratified sampling.

Notation. Index. Contents.


















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