A positivity-preserving projection Euler scheme for α-stable driven linear volatility models converges with strong order 1/α in L^q for q < α.
A positivity preserving numerical scheme for the alpha-CEV process
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abstract
In this article, we present a method to construct a positivity-preserving numerical scheme for a jump-extended CEV (Constant Elasticity of Variance) process, whose jumps are governed by a spectrally positive $\alpha$-stable process with $\alpha \in (1,2)$. The numerical scheme is obtained by making the diffusion coefficient $x^\gamma$, where $\gamma \in (\frac{1}{2},1)$, partially implicit and then finding the appropriate adjustment factor. We show that, for sufficiently small step size, the proposed scheme converges and theoretically achieves a strong convergence rate of at least $\frac{1}{2}\left(\frac{\alpha_-}{2} \wedge \frac{1}{\alpha}\wedge \rho\right)$, where $\rho \in (\frac{1}{2},1)$ is the H\"older exponent of the jump coefficient $x^\rho$ and the constant $\alpha_- < \alpha$ can be chosen arbitrarily close to $\alpha \in (1,2)$.
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Explicit positivity preserving numerical method for linear stochastic volatility models driven by $\alpha$-stable process
A positivity-preserving projection Euler scheme for α-stable driven linear volatility models converges with strong order 1/α in L^q for q < α.