DCC vs CCC GARCH models

Question

What is the difference b/w the GARCH models. I understand that these measure volatility spillover effects but i dont understand these properly.

Could it be possible to measure volatility/traffic of Reddit comments/posts relative to cryptocurrency volumes (or cryptocurrency returns(i.e. volatility), which would be calculated in percentage).

Or if someone has a better recommendation, I love to hear it.

Thanks in advance

Answer 1

The differences between CCC and DCC should be clear from the papers that introduced DCC as an extension of CCC: Engle & Sheppard (2001) and Engle (2002). They are also discussed in time series textbooks that cover multivariate GARCH models such as Lütkepohl (2005) (chapter 16) and Tsay (2013) (chapter 7). The essential difference is that in CCC, the conditional correlation matrix of the residuals from the conditional mean model is constant over time, while in DCC, it is time varying in a an autoregressive (more precisely, GARCH-like) manner.

Neither CCC nor DCC can model volatility spillovers. Some articles may claim otherwise, but as far as I can tell that just shows a lack of understanding of the mechanics of these models.

References:

• Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350.
• Engle III, R. F., & Sheppard, K. (2001). Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH.
• Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer Science & Business Media.
• Tsay, R. S. (2013). Multivariate time series analysis: with R and financial applications. John Wiley & Sons.