A multivariate Ornstein-Uhlenbeck type stochastic volatility model

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THE MULTIVARIATE supOU STOCHASTIC VOLATILITY MODEL (2013, methodology): “The relevance of these results is that they provide the basis for (general) method of moments-based estimation of the model as in Pigorsch and Stelzer (2009a) for the multivariate SVOU model and Barndorff-Nielsen and Shephard (2011) for the univariate SVsupOU model.”
On strong solutions for positive definite jump diffusions (2009, unknown): “• The usual tensor (Kronecker) product of two matrices A,B is denoted by A⊗B and the vectorisation operator mapping Md to Rd 2 by stacking the columns of a matrix A below each other is denoted by vec(A) (see [29, Chapter 4] for more details).”
Multivariate supOU processes (2010, methodology): “Then it follows by similar arguments as in [36, 41] that E(e ∗ t |Y0) = exp { i(Y0 + μt)∗u + ∫ M− d ∫ t −∞ φ [ e ∗(t−s) ( A(A)−∗ ( uβ∗ + i 2 uu∗ )) eA(t−s) (5.”