Quantitative Analysis.
Trading Platform.
Python for Excel.
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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.
A.Gram-Schmidt orthogonalization.
B.Definition and existence of orthogonal polynomials.
C.Three-term recurrence relation for orthogonal polynomials.
D.Orthogonal polynomials and quadrature rules.
E.Extremal properties of orthogonal polynomials.
F.Chebyshev polynomials.
3.Asymptotic expansions.
4.Generation of random samples.
5.Monte-Carlo.
6.Convex Analysis.
VI.Basic Math II.
VII.Implementation tools II.
Bibliography.
Forum Notation Index Contents

Gauss-Hermite Integration.


he following is an extremely efficient integration formula:

MATH(Gauss-Hermite Intergration)
MATH Note that one can do the change of function MATH to obtain more generic result.

The below values of $w_{i},x_{i}$ are taken from [Abramowitz], pages 890 and 924:MATHMATHMATH What follows next is a fragment of theory of orthogonal polynomials that leads to the formula ( Gauss-Hermite Intergration). The proposition ( Gaussian quadrature rule) provides the justification. There are several sections after ( Gaussian quadrature rule) included for their importance for other applications within these Notes. The reference is [Gautschi].




A.Gram-Schmidt orthogonalization.
B.Definition and existence of orthogonal polynomials.
C.Three-term recurrence relation for orthogonal polynomials.
D.Orthogonal polynomials and quadrature rules.
E.Extremal properties of orthogonal polynomials.
F.Chebyshev polynomials.

Forum Notation Index Contents


















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