A new covariance matrix estimator is proposed under the assumption that at every time period all pairwise correlations are equal. This assumption, which is pragmati- cally applied in various areas of finance, makes it possible to estimate arbitrarily large covariance matrices with ease. The model, called DECO, is a special case of the CCC and DCC models which involve first adjusting for individual volatilities and then estimating the correlations. A QMLE result shows that DECO can continue to give consistent parameter estimates when the equicorrelation assumption is violated. Generalizations to block equicorrelation structures, models with exogenous variables, and alternative specifications are explored and diagnostic tests are proposed. Es...
The increasing availability of high-quality transaction data across many financial assets, allow the...
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dime...
New dynamic models for realized covariance matrices are proposed. The expected value of the realized...
A new covariance matrix estimator is proposed under the assumption that at every time period all pai...
This article provides the first empirical application of the dynamic equicorrelation (DECO) model to...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
This paper develops time series methods for forecasting correlations in high dimensional problems. T...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
In this paper, we develop the theoretical and empirical properties of a new class of multivariate GA...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
In this paper, we develop the theoretical and empirical properties of a new class of multi-variate G...
One of the most widely-used multivariate conditional volatility models is the dynamic conditional c...
Large one-off events cause large changes in prices, but may not affect the volatility and correlatio...
Second moments of asset returns are important for risk management and portfolio selection. The probl...
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dime...
The increasing availability of high-quality transaction data across many financial assets, allow the...
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dime...
New dynamic models for realized covariance matrices are proposed. The expected value of the realized...
A new covariance matrix estimator is proposed under the assumption that at every time period all pai...
This article provides the first empirical application of the dynamic equicorrelation (DECO) model to...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
This paper develops time series methods for forecasting correlations in high dimensional problems. T...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
In this paper, we develop the theoretical and empirical properties of a new class of multivariate GA...
Time varying correlations are often estimated with Multivariate Garch models that are linear in squa...
In this paper, we develop the theoretical and empirical properties of a new class of multi-variate G...
One of the most widely-used multivariate conditional volatility models is the dynamic conditional c...
Large one-off events cause large changes in prices, but may not affect the volatility and correlatio...
Second moments of asset returns are important for risk management and portfolio selection. The probl...
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dime...
The increasing availability of high-quality transaction data across many financial assets, allow the...
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dime...
New dynamic models for realized covariance matrices are proposed. The expected value of the realized...