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In the case of application in finance, usually, GARCH is used in estimating realized volatility of returns based on the weight we would like to give to each past observation. Ultimately after estimating (calibrating) the parameters of the model to an existing time-series, GARCH is used for forecasting multi-step ahead return (future) volatility. Different ...


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I am not sure to understand your question. But as far as I understand it. If you have a dataset with $Y,K,L,M$ over a set of corporates over some years, you can estimate $A$ using a log-log regression, since the following model is compatible with your Coob-Douglas specification: $$\log Y=a \log K + b \log L + c \log M + \log A.$$ It is clearly the ...


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For Engle-Granger, I can see that you are returned a vector of 2 elements for each of the output arguments, hence you run two tests there. For the sake of clarity and the education of people interested in the post, we can say that: Since your $hValues$ are both zero, we can say that there is a failure to reject the Null Hypothesis, which in this case is ...



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