In this work we will describe methods for modeling multivariate financial time series. We will concentrate on both modeling expected value by multi- variate Box-Jenkins processes and primarily on modeling conditional corre- lations and volatility. Our main object will be DCC (Dynamic Conditional Correlation) model, estimation of its parameters and some other general- izations. Then we will programme DCC model in statistical software R and apply on real data. In applications we will concentrate on problem of high dimension of financial time series and on modeling conditional correlations data with outliers
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
The dependence structure in multivariate financial time series is of great importance in portfolio m...
[[abstract]]This study blends the simplicity and empirical success of univariate GARCH processes wit...
In this work we will describe methods for modeling multivariate financial time series. We will conce...
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) ...
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) ...
Research projects in the area of multivariate financial time-series are of a particular interest for...
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in ...
This article presents theoretical and empirical methodology for estimation and modeling of multivari...
The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Car...
Title: Selected problems of financial time series modelling Author: Radek Hendrych Department: Depar...
Forecasting volatility in a multivariate framework has received many contributions in the recent li...
One of the main problems in modelling multivariate conditional covariance time series is the paramet...
© 2020 Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015. All right...
This paper generalizes the Dynamic Conditional Correlation (DCC) model of Engle (2002), incorporatin...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
The dependence structure in multivariate financial time series is of great importance in portfolio m...
[[abstract]]This study blends the simplicity and empirical success of univariate GARCH processes wit...
In this work we will describe methods for modeling multivariate financial time series. We will conce...
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) ...
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) ...
Research projects in the area of multivariate financial time-series are of a particular interest for...
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in ...
This article presents theoretical and empirical methodology for estimation and modeling of multivari...
The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Car...
Title: Selected problems of financial time series modelling Author: Radek Hendrych Department: Depar...
Forecasting volatility in a multivariate framework has received many contributions in the recent li...
One of the main problems in modelling multivariate conditional covariance time series is the paramet...
© 2020 Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015. All right...
This paper generalizes the Dynamic Conditional Correlation (DCC) model of Engle (2002), incorporatin...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
The dependence structure in multivariate financial time series is of great importance in portfolio m...
[[abstract]]This study blends the simplicity and empirical success of univariate GARCH processes wit...