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Does anyone know a way adjust the parameters in the VARMA model so that the h-step forecast satisfy some given expected values, standard deviations and correlations while changing the model as little as possible so that it is close to the historical data?

So far I have read about a method where the sampled forecast density of the VARMA model is re-weighted to satisfy the "view" (expected values, standard deviations and correlations) by minimizing the relative entropy between the forecast distribution from the VARMA model and the adjusted forecast distribution. However, I would instead like to change the model in a way so that the "view" is satisfied.

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