Comments (4)
Did you check out the paper?
Quoting myself from a previous issue
y
is price relative vector for two adjacent price vector(v_t
&v_{t-1}
) while Eq. (18) states the normalization of the price in the training set. You can see the normalization code for y and for X
Maybe this will help a bit.
from pgportfolio.
thanks,
normalization code for y - ok
but for X - 404
from pgportfolio.
but for X - 404
for X it's done at batch training, in code
network = network / network[:, :, -1, 0, None, None]
So to put in simple words, it's the batch of relative prices divided by the last period of the relative price.
from pgportfolio.
understood thanks!
from pgportfolio.
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