In the empirical analysis of financial time series, multivariate GARCH models have been used in various forms. In most cases it is not well understood how the use of a restricted model has to be paid with loss of valuable information. We investigate the structural implications of two alternative models for the response of the conditional (co-)variances to independent shocks. The impulse response analysis, adopted to volatility models, appears to be a convenient methodology to obtain information on the interaction of financial series. We define volatility impulse response functions and provide an empirical analysis for a bivariate exchange rate series. For the analyzed series, the impulse response function of the correlation reveals strong ...
We introduce a multivariate GARCH model that incorporates realized measures of volatility and covol...
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in ...
© 2014. We examine how the most prevalent stochastic properties of key financial time series have be...
In the empirical analysis of financial time series, multivariate GARCH models have been used in vari...
This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multiva...
This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multiva...
This study introduces volatility impulse response functions (VIRF) for dynamic conditional correlati...
This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (201...
This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spill...
Volatility impulse response functions (VIRFs) have been introduced to unravel the effects of shocks ...
This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spill...
The dissertation consists of three studies concerning the research fields of evaluating volatility a...
We estimate the data generating process of daily excess returns of 20 major German stocks in a CAPM ...
The class of multivariate GARCH models is widely used to quantify and monitor volatility and correla...
After the so-called Asia crisis in the summer of 1997 the stock markets were shaken by an increased ...
We introduce a multivariate GARCH model that incorporates realized measures of volatility and covol...
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in ...
© 2014. We examine how the most prevalent stochastic properties of key financial time series have be...
In the empirical analysis of financial time series, multivariate GARCH models have been used in vari...
This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multiva...
This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multiva...
This study introduces volatility impulse response functions (VIRF) for dynamic conditional correlati...
This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (201...
This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spill...
Volatility impulse response functions (VIRFs) have been introduced to unravel the effects of shocks ...
This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spill...
The dissertation consists of three studies concerning the research fields of evaluating volatility a...
We estimate the data generating process of daily excess returns of 20 major German stocks in a CAPM ...
The class of multivariate GARCH models is widely used to quantify and monitor volatility and correla...
After the so-called Asia crisis in the summer of 1997 the stock markets were shaken by an increased ...
We introduce a multivariate GARCH model that incorporates realized measures of volatility and covol...
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in ...
© 2014. We examine how the most prevalent stochastic properties of key financial time series have be...