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
1 | CCCgarch.MM(R, momentargs = NULL, ...)
|
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 |
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