Okay, it seems to work with Mahalanobis:
b = (X′S^−1X)−1X′S^−1Y minimizes the Mahalanobis-distance of Xb to Y .
And S is the covariance-matrix.
cov = a0+a1x_{n-1}*y_{n-1}+ß*cov{n-1}
But shouldn´t it be the covariance of the residuals?
Anyone experiences with that?
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Hey Guys,
i want to do a CAPM-GARCH model. I didn´t find anything posted online.
(If there is something - shame on me - i didn´t find it.)
My Problem: What is the difference if I let the residuals “e” follow a
garch process ?
How do I do my regression analysis now? I began
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