The Vector Autoregressive (VAR) model with zero coefficient restrictions can be formulated as a Seemingly Unrelated Regression Equation (SURE) model. Both the response vectors and the coefficient matrix of the regression equations comprise columns from a Toeplitz matrix. Efficient numerical and...

Closed form approximations to the fundamental solution of parabolic PDEs is considered. The approach consists on approximations based on a parametrix series expansion. The approximation error can be bounded by a gaussian function and it is of an order of t^2. These explicit expressions have...

The Hobson and Rogers model for option pricing is considered. This stochastic volatility model preserves the completeness of the market and can potentially reproduce the observed smile and term structure patterns of implied volatility. A calibration procedure based on ad-hoc numerical schemes...

The path-dependent volatility model by Hobson and Rogers is considered. It is known that this model can potentially reproduce the observed smile and skew patterns of different directions, while preserving the completeness of the market. In order to quantitatively investigate the pricing...

Vector Autoregressive processes of order p (VAR(p)) with coefficient restrictions can be formulated as a SURE model. The response vectors and the coefficient matrices of the regression equations comprise columns from a Toeplitz matrix. Numerical and computational methods that solve the SURE...

The Vector Autoregressive (VAR) model with zero coefficient restrictions canbe formulated as a Seemingly Unrelated Regression Equation (SURE) model. Boththe response vectors and the coefficient matrix of the regression equationscomprise columns from a Toeplitz matrix. Efficient numerical and...