Quantitative Analysis.
Trading Platform.
Python for Excel.
Author.

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I.Basic math.
II.Pricing and Hedging.
III.Explicit techniques.
1.Black-Scholes formula.
2.Change of variables for Kolmogorov equation.
3.Mean reverting equation.
4.Affine SDE.
5.Heston equations.
6.Displaced Heston equations.
7.Stochastic volatility.
A.Recovering implied distribution.
B.Local volatility.
C.Gyongy's lemma.
D.Static hedging of European claim.
E.Variance swap pricing.
8.Markovian projection.
9.Hamilton-Jacobi Equations.
IV.Data Analysis.
V.Implementation tools.
VI.Basic Math II.
VII.Implementation tools II.
Bibliography.
Forum Notation Index Contents

Local volatility.


uppose the stock follows the SDEMATHMATH in the risk neutral world. The MATH is a deterministic function of time. The $t_{0}$ is the moment of observation. We aim to express the volatility MATH as a function of MATH and its derivatives with respect to strike.

We use the representationMATH in terms of distribution density MATH We calculate the $T$-derivativeMATH and substitute the ( Forward_Kolmogorov):MATHMATH

We evaluate each integral via integration by parts and with help of results ( Distribution density via Call). MATHMATH

Summary

AssumeMATH thenMATH





Forum Notation Index Contents


















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