Economics at your fingertips  

Multivariate Garch with dynamic beta

Matthias Raddant and Friedrich Wagner

Papers from

Abstract: We present a solution for the problems related to the application of multivariate Garch models to markets with a large number of stocks by restricting the form of the covariance matrix. It contains one component describing the market and a second simple component to account for the remaining contribution to the volatility. This allows the analytical calculation of the inverse covariance matrix. We compare our model with the results of other Garch models for the daily returns from the S&P500 market. The description of the covariance matrix turns out to be similar to the DCC model but has fewer free parameters and requires less computing time. The model also has the advantage that it contains the calculation of dynamic beta values. As applications we use the daily values of $\beta$ coefficients available from the market component to confirm a transition of the market in 2006. Further we discuss the relationship of our model with the leverage effect.

New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2016-09, Revised 2019-08
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Papers from
Bibliographic data for series maintained by arXiv administrators ().

Page updated 2019-10-29
Handle: RePEc:arx:papers:1609.07051