DA-RNN-in-Tensorflow-2-and-PyTorch
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Are multi-step predictions possible?
Hey,
thanks for providing this nice library! :)
Running your example I was wondering if it is possible to change the length of the predictions. As far as I have seen, only a prediction of length 1 is produced. But for my thesis I would like to forecast up to 96 time-steps into the future...
Would that be possible and if yes could you provide an example?
Thanks in advance and have a great day!
Generally, there are two kinds of multi-step predictions:
- single-shot model: it is controlled by
y_dim. For example, if you want to do 2-step no-shift predictions, you are required to preprocess training data withy_dim=2 - autoregressive model: it is not mentioned in the paper, and
da_rnndoes not support regression and it only could predicty_T_hat, see here.
Besides, IMO, time-series prediction is a very bad way to do quant trading and multi-step predictions will bring even worse results.
I think a 96 time-step prediction will be worse than doing nothing.