The intertemporal capital asset pricing model of Merton (1973) is examined using the dynamic conditional correlation (DCC) model of Engle (2002). The mean-reverting DCC model is used to estimate a stock's (portfolio's) conditional covariance with the market and test whether the conditional ...
We introduce a new specification of the dynamic conditional correlation (DCC) model, where its parameters are estimated with the use of closing and additionally low and high prices. Such prices are often commonly available for many financial series and contain more information about the variation of...
The unconditional CAPM fails, but the conditional CAPM with dynamic conditional correlations (DCC) succeeds in generating a significantly positive risk-return tradeoff. The conditional alpha estimates indicate that the time-varying conditional covariances explain the industry, size and value premiums, but...
In this paper Dynamic Conditional Correlation (DCC) estimators are proposed that have the flexibility of univariate GARCH but not the complexity of conventional multivariate GARCH. These models, which parameterize the conditional correlations directly, are naturally estimated in two steps –the first...
A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two...
InthispaperDynamicConditionalCorrelation(DCC)estimatorsareproposedwhichhavetheflexibilityofunivariateGARCHbutnotthecomplexityofmultivariateGARCH.Thesemodels,whichparameterizetheconditionalcorrelationsdirectly,arenaturallyestimatedintwosteps–thefirstisaseriesofunivariateGARCHestimatesand thesecondthecorrelationestimate. Thenext...
Conditional correlations between S&P 500 index and the component stocks increase substantially during the period of sub-prime crisis, showing strong evidence of contagion. In addition, stock return variance is time-varying and peaks at the crest of financial crisis. The results show that the DCC-...
aFor the model development, we first predefined 20 seed regions within the DMN based on ref.35. We then calculated the Dynamic Conditional Correlation (DCC) between each seed region and 280 Brainnetome-based parcels using rsfMRI data from 84 participants. Using the variance of DCC time-series ...
and wartime data covering the period from January 2010 to May 2022, The commodity and securities markets are considered, and the dynamic correlation between the volatilities of different financial markets is measured using the dynamic conditional correlation (DCC) based on the multivariate GARCH model....
Fourth, it can produce smooth patterns for the correlations. We also present an empirical application to exchange rate time series which illustrates that it can have a better fit of the data than the dynamic conditional correlation (DCC) model recently proposed in Engle (2002). The model of ...