This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and...

This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1) and I(2) models are considered. The performance of algorithms is compared first in terms of effectiveness, defined as...

This note examines the accuracy of methods that are commonly used to approximate AR(1)-processes with discrete Markov chains. The quadrature-based method suggested by Tauchen and Hussey (1991) generates excellent approximations with a small number of nodes when the autocorrelation is low or...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

Oil-macro-financial linkages in Saudi Arabia are analyzed by applying panel econometric frameworks (multivariate and vector autoregression) to maceoeconomic and bank-level balance sheet data for 9 banks spanning 1999-2014. Lower growth of oil prices and non-oil private sector output leads to...

Vector autoregressive models are increasingly being used in the analysis of relationships within and between financial markets. In such models, there are circumstances that require zero entries in the coefficient matrices. Such circumstances can be particularly relevant in the context of markets...

Vector error-correction models (VECM) are increasingly being used to capture dynamic relationships between financial variables. Estimation and interpretation of such models can be enhanced if zero restrictions are allowed in the coefficient matrices. Specifically, in tests of indirect causality...

We present a new technique for obtaining a positive definite (PD) correlation matrix from a stressed target matrix within the context of Advanced Stressed Value at Risk, (cf. Dash ). The technique uses the spherical decomposition and a “nearest neighbor” technique. The advantage is that...