CCCgarch.MM: compute comoments for use by lower level optimization...
In PortfolioAnalytics: Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios
Description
it first estimates the conditional GARCH variances, then filters out the
time-varying volatility and estimates the higher order comoments on the innovations
rescaled such that their unconditional covariance matrix is the conditional covariance matrix forecast
Usage
1
CCCgarch.MM(R, momentargs = NULL, ...)
Arguments
R
an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
momentargs
list containing arguments to be passed down to lower level functions, default NULL
...
any other passthru parameters
PortfolioAnalytics documentation built on May 2, 2019, 6:12 p.m.
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Description
it first estimates the conditional GARCH variances, then filters out the time-varying volatility and estimates the higher order comoments on the innovations rescaled such that their unconditional covariance matrix is the conditional covariance matrix forecast
Usage
1 | CCCgarch.MM(R, momentargs = NULL, ...)
|
Arguments
R |
an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns |
momentargs |
list containing arguments to be passed down to lower level functions, default NULL |
... |
any other passthru parameters |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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