We propose a generalization of the Dynamic Conditional Correlation multivariate GARCH model of Engle (2002) and of the Asymmetric Dynamic Conditional Correlation model of Cappiello et al. (2006). The model we propose introduces a block structure in parameter matrices that allows for interdependence with a reduced number of parameters. Our model nests the Flexible Dynamic Conditional Correlation...

We estimate the risk spillover among European banks from equity log-return data via Conditional Value at Risk (CoVaR). The joint dynamic of returns is modeled with a spatial DCC-GARCH which allows conditional variance log-returns each bank to depend on past volatility shocks other and their squared in parsimonious way. backtesting resulting measures provides evidence that (i) multivariate GARCH...

ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper surveys the semiparametric and nonparametric methods in univariate andmultivariate ARCH/GARCHmodels. First, we introduce some specific semiparametric models and investigate the semiparametric and nonparametrics estimation techniques applied to: the error density, the functional form of the volatil...

Value-at-Risk has become one of the most widely-used financial risk measurement techniques. In this paper, we compare multivariate and univariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models in terms of their respective performance in forecasting portfolio Value-at-Risk (VAR). First, we review a few common VaR models both in a univariate and a multivariate setting. T...

Predicting the “Value at Risk” of a portfolio of stocks is of great significance in quantitative finance. We introduce a new class models, “dynamical products of experts” that treats the latent process over volatilities as an inverse Gamma process. We show that our multivariate volatility models significantly outperform all related Garch and stochastic volatility models which are in popular use...

Fossil energy markets have always been known as strategic and important markets. They have a significant impact on the macro economy and financial markets of the world. The nature of these markets are accompanied by sudden shocks and volatility in the prices. Therefore, they must be controlled and forecasted by using appropriate tools. This paper adopts the Generalized Auto Regressive Condition...