Modelling Realized Covariances
This paper proposes a new dynamic model of realized covariance (RCOV) matrices based on recent work in time-varying Wishart distributions. The specifications can be linked to returns for a joint multivariate model of returns and covariance dynamics that is both easy to estimate and forecast. Realized covariance matrices are constructed for 5 stocks using high-frequency intraday prices based on positive semi-definite realized kernel estimates. We extend the model to capture the strong persistence properties in RCOV. Out-of-sample performance based on statistical and economic metrics show the importance of this. We discuss which features of the model are necessary to provide improvements over a traditional multivariate GARCH model that only uses daily returns.
|Date of creation:||10 Nov 2009|
|Contact details of provider:|| Postal: 150 St. George Street, Toronto, Ontario|
Phone: (416) 978-5283
When requesting a correction, please mention this item's handle: RePEc:tor:tecipa:tecipa-382. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RePEc Maintainer)
If references are entirely missing, you can add them using this form.