CCCgarch.MM: compute comoments for use by lower level optimization...
In R-Finance/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
R-Finance/PortfolioAnalytics documentation built on May 8, 2019, 4:46 a.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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