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
We shall say that an approximation process Y converges in the strong sense with order γ ε (0, ∞] with a continuous process X if there exists a finite constant K and a positive constant δ0 such that:
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for any time discretization of T with maximum step size δ ε (0, δ0).
In this section, we present the strong stochastic Taylor schemes of orders 0.5, 1.0 and 1.5 for the N-dimensional Ito SDE with an M-dimensional Wiener process {3} as well as the strong order 2.0 stochastic Taylor scheme for the corresponding Stratonovich SDE.
Euler scheme
The strong stochastic Taylor scheme of order 0.5 for the {SDE-3}, usually called the stochastic Euler scheme, has the component-wise form:
(9)
f or i = 1, ..., N ; j = 1, ..., M
where ∆n = tn+1 − tn is the length of the nth time step and ∆Wjn = Wjn+1 −Wjn is the N(0, ∆n)−distributed increment of the jth component of the M-dimensional standard Wiener process Wt on the discretization subinterval [tn, tn+1]. Here ∆W j1 n and ∆W j2 n are independent for j1 ? j2.
Milstein scheme
The strong stochastic Taylor scheme of order 1.0 for the {SDE-3}, usually called the Milstein scheme, has the component-wise form:
(10)
f or i = 1, ..., N ; j = 1, ..., M
where I(j1,j2);n is the multiple Ito integral:

These double integrals have the following properties:
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(11)
for: j1 ≠ j2.
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