This paper introduces an extended multivariate EGARCH model that overcomes the zero-return problem and allows for … negative news and volatility spillover effects, making it an attractive tool for multivariate volatility modeling. Despite … empirical examples demonstrate the model's superior performance compared to multivariate GJR-GARCH and Log-GARCH models in …

This paper extends the multivariate filter approach for estimating potential output and NAIRU developed for Türkiye by …

This paper presents a credit gap for Malta derived from a semi-structural multivariate filter. This modelling approach … has several advantages over univariate approaches typically used, for example to construct the Basel gap. The multivariate …

This study introduces a multivariate extension to the class of stochastic volatility models, employing integrated … aims to establish a computationally efficient approach for estimating multivariate stochastic volatility models. We propose …

-called multivariate conditional value-at-risk (MCoVaR), which measures the tail risk of a targeted asset from each market conditional on a …. In this paper, we aimed to find its analytic formulas by considering multivariate copulas, which allow for the separation … of margins and dependence structures in modeling the returns of the aforementioned assets. Compared to multivariate …