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This post suggests that we use eigen values to determine the half life of reverting to mean :

https://quant.stackexchange.com/questions/2076/how-to-interpret-the-eigenmatrix-from-a-johansen-cointegration-test

I have read in many places that the alpha matrix represents the speed of adjustment.

I read in another place that the eigenvalue is approximately equal to the "alpha" parameter.

Here is a counter example :-

https://www.quantstart.com/articles/Johansen-Test-for-Cointegrating-Time-Series-Analysis-in-R

The eigen value is .0038. None of the values in the alpha (loading matrix) are close to this.

Give a VECM with a alpha matrix, how do I compute the half life ? In case we have only ONE regression we do ln(2)/alpha.

My query is how do we go from the alpha matrix to the half life in the case when alpha is a matrix ?

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