Strong Taylor Schemes for Stochastic Volatility
Ito and Stratonovich Stochastic Calculus
Ito-Stratonovich drift conversion
Strong Numerical Schemes for SDE
Milstein scheme for commutative noise
Approximations of Volatility Models
General 2D Milstein scheme for stochastic volatility models
Approximations of the Double Integral
Subdivision (Kloeden - IC = 0)
Simulation of the Double Integral
Formulae derivation for Heston Volatility
Derivation of the 2D Milstein Scheme
Suppose that we can find the solution of the PDE, say G(w, ν, τ ), with the property that at t = T , G(w, ν, 0) = 1. Then the solution to the transformed PDE {48} with payoff condition U (w, ν, 0) is just the product of this with G.
(49)
Lewis (refer to [11]) discusses how to solve {49} for the general case, but here we will only solve for the Heston model (γ = 1/ 2 ).
Greeks for free
Before figuring out G, we should point out that {49} is a remarkably useful representation. If you want to differentiate V with respect to S to obtain ∆, you merely multiply the integral by:
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and for Γ, the integral is multiplied by:
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This representation also makes obvious the link between ρ and ∆.
Finding the fundamental solution
For γ = 1/ 2 and Heston parameters, the PDE {48} yield the form:
(50)
What Heston [6] does is try to find a solution in the form:
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with:
A [0, w] = B [0, w] = 0
in order to satisfy the condition that G[0, w] = 1 (at maturity). If we substitute this assumption for the form of G into the PDE {50}, we obtain the following condition:
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The A' and B' denote the τ − derivative. This must be true for all ν so we separately equate the terms that are independent of ν and linear in ν to obtain the pair of ordinary differential equations:

Solving this, we obtain:

where:

So the exact solution of the option price using Heston volatility is:
(51)
using the condition:
for
Call options Im(w) > 1
Put options Im(w) < 0
For further information or more details, see [16] or [6].
Prof. Klaus Schmitz

Strong Taylor Schemes for Stochastic Volatility
This method requires formulas that are not always easy or possible to find. In this document, we present the corresponding approximations for both Euler and Milstein schemes for the usual Geometric Brownian Motion and the stochastic volatility models. Also, we present five methods of how we can simulate the double integrals for the 2 dimensional Milstein approximation.
By Prof. Klaus Erich Schmitz Abe