varcov {LFUrmutils} | R Documentation |
Function to extract the variance-covariance matrix of multivariate volatility models. Currently only implemented for models of class MultiEWMA
.
varcov(object, ...) ## S3 method for class 'MultiEWMA' varcov(object, offdiagonal = TRUE, duplicates = TRUE, ...)
object |
Output of a multivariate volatility model. |
offdiagonal |
Whether diagonal elements should be kept or not. |
duplicates |
Whether duplicate off-diagonal elements should be kept or not. |
... |
Arguments passed to methods. |
Returns the variance-covariance matrix of a multivariate volatility model.
A multivariate zoo
object. Each row of the output objects represents the correlation matrix (or elements thereof) of the corresponding day.
If the full conditional variance-covariance matrices are needed, users can also use fitted
, which is slightly faster. However, in comparison to fitted
, varcov
gives the user more control over the extracted elements of the conditional variance-covariance matrices. Moreover, in future releases of this package, varcov
may be defined for other multivariate volatility models as well. In this case, the function will provide a convenient infrastructure to better compare the output of these models.
Bernhard Eder
Danielsson (2011). Financial Risk Forecasting. Wiley. Chichester.
Jorion (2007). Value at Risk, 3rd. McGraw-Hill. New York.
Ruppert and Matteson (2015). Statistics and Data Analysis for Financial Engineering, 2nd. Springer. New York.
# Load returns data("CRSPday_zoo") y <- CRSPday_zoo # Compute multivariate EWMA model ewma <- MultiEWMA(y, center = TRUE) # Extract variance covariance matrix EWMAvc <- varcov(ewma) plot(EWMAvc)