ENH: allow exogenous variable to be numpy 2-d array

[lfdmotta]

Hi,
I'd like to suggest that the forecast method of the arch model result be capable of accepting exogenous variables as (horizon, scenario), 2d numpy array. Right now, the solution with a for-loop for every scenario x does not take advantage of matrix multiplication that can be done more efficiently:

$$ y_{t+1, i_scenario} = \beta 1_{i_scenario, j_scenario} x_{t+1, j_scenario} + \ldots $$

and this slows down computations considerably for someone calculating simulations for several paths and several time-series $y_t$ for a single task, say if one wants to look at several risk factors that have an exogenous systemic risk factor.

This would be useful if the output includes y_t for each scenario (not only unconditional means).

[bashtage]

This can't work since exogenous variables are already 2d since AR-X can have multiple X, and so you have to be able to pass 2-d for specify the values of all X's. I think this is probably too specialized a request to get in, especially since you want to have multiple parameter values and multiple x-values.

[lfdmotta]

It's a feature available in rugarch package and it seems very useful for anyone working in finance. In rugarch it accepts a list of data frames, the list has the length equal to the number of external regressors. In python it could be a 3d numpy array.

[bashtage]

I'm open to a PR but am unlikely to implement this myself.