Oil market VAR models have become the standard tool for understanding evolution of real price oil and its impact on macro economy. As this literature has expanded at a rapid pace, it increasingly difficult mainstream economists to understand differences between alternative models, let alone basis sometimes divergent conclusions reached in literature. The purpose survey is provide guide Our focu...

In cointegrated vector autoregressive (VAR) analyses various nonlinear functions of the co-eecients are of interest. Notable examples are impulse responses. A general theory for asymptotic inference on such functions is developed under the assumption that the actual data generation process (DGP) is of potentially innnite VAR order although nite order VAR models are tted to the data and are used...

In accordance with Basel Capital Accords, the Capital Requirements (CR) for market risk exposure of banks is a nonlinear function of Value-at-Risk (VaR). Importantly, the CR is calculated based on a bank’s actual portfolio, i.e. the portfolio represented by its current holdings. To tackle mean-VaR portfolio optimization within the actual portfolio framework (APF), we propose a novel mean-VaR op...

This paper proposes a Bayesian procedure for combining forecasts from multivariate forecasting models, e.g. VAR models. Standard applications of Bayesian model averaging suffer from a basic difficulty in this context, when additional variables are included and modelled the connection between the overall measure of fit for the model and the expected forecasting performance for the variables of i...