A small strand of recent literature is occupied with identifying simultaneity in multiple equation systems through autoregressive conditional heteroscedasticity. Since this approach assumes that the structural innovations are uncorrelated, any contemporaneous connection of the endogenous variables needs to be exclusively explained by mutual spillover effects. In contrast, this paper allows for instantaneous covariances, which become identifiable by imposing the constraint of structural constant / dynamic conditional correlation (SCCC / SDCC). In this, common driving forces can be modelled in addition to simultaneous transmission effects. The methodology is applied to the Dow Jones and Nasdaq Composite indexes, illuminating scope and functio...
In this dissertation, I analyze determinants of conditional correlations. Specifically, I propose th...
In this report we examine time-varying correlations of asset returns using the Dynamic Conditional C...
summary:One of the most widely-used multivariate conditional volatility models is the dynamic condit...
A small strand of recent literature is occupied with identifying simultaneity in multiple equation s...
A small strand of recent literature is occupied with identifying simultaneity in multiple equation s...
In the literature of identifcation through autoregressive conditional heteroscedasticity, Weber (200...
In the literature of identication through autoregressive conditional heteroscedasticity, Weber (2008...
This paper seeks to disentangle the sources of correlations between high-, mid- and lowcap stock ind...
This paper disentangles direct spillovers and common factors as sources of correlations in simultane...
We analyze whether the crisis sourced in US is spread over the world by contagion or through interde...
This paper shows how the dependency of time-varying conditional crosscorrelation on prevailing marke...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
One of the most widely-used multivariate conditional volatility models is the dynamic conditional c...
This paper assesses the economic value of modeling conditional correlations for mean–variance portfo...
In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilit...
In this dissertation, I analyze determinants of conditional correlations. Specifically, I propose th...
In this report we examine time-varying correlations of asset returns using the Dynamic Conditional C...
summary:One of the most widely-used multivariate conditional volatility models is the dynamic condit...
A small strand of recent literature is occupied with identifying simultaneity in multiple equation s...
A small strand of recent literature is occupied with identifying simultaneity in multiple equation s...
In the literature of identifcation through autoregressive conditional heteroscedasticity, Weber (200...
In the literature of identication through autoregressive conditional heteroscedasticity, Weber (2008...
This paper seeks to disentangle the sources of correlations between high-, mid- and lowcap stock ind...
This paper disentangles direct spillovers and common factors as sources of correlations in simultane...
We analyze whether the crisis sourced in US is spread over the world by contagion or through interde...
This paper shows how the dependency of time-varying conditional crosscorrelation on prevailing marke...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
One of the most widely-used multivariate conditional volatility models is the dynamic conditional c...
This paper assesses the economic value of modeling conditional correlations for mean–variance portfo...
In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilit...
In this dissertation, I analyze determinants of conditional correlations. Specifically, I propose th...
In this report we examine time-varying correlations of asset returns using the Dynamic Conditional C...
summary:One of the most widely-used multivariate conditional volatility models is the dynamic condit...