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Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
Services
Author
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I. Basic math.
II. Pricing and Hedging.
III. Explicit techniques.
IV. Data Analysis.
V. Implementation tools.
1. Finite differences.
A. Finite difference basics.
B. One dimensional heat equation.
C. Two dimensional heat equation.
D. General techniques for reduction of dimensionality.
E. Time dependent case.
2. Gauss-Hermite Integration.
3. Asymptotic expansions.
4. Monte-Carlo.
5. Convex Analysis.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Finite differences.


inite differences is an obsolete technique. See the chapter ( Finite elements ). It has problems, see the section ( Remark on stability of financial problems ). It lacks efficiency of approximation, see the section ( Wavelet analysis ). However, it is also a very simple technique. It is applicable in context of model validation. In addition, there is much of legacy code around that uses finite differences (and even binary trees) and needs support.




A. Finite difference basics.
B. One dimensional heat equation.
C. Two dimensional heat equation.
D. General techniques for reduction of dimensionality.
E. Time dependent case.

Notation. Index. Contents.


















Copyright 2007