Adv_Fin_ML_Exercises
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getWeights_FFD is incomplete!
As defined in the book the FFD approach of getWeights which is Xt =Σl∗k=0 𝜔̃ kXt−k,
uses k which is k = 0,…, T − 1.
Thus a limit/size parameter is requried for getWeights_FFD in notebook 05. Fractionally Differentiated Features!
A complete implementation can be found at
https://github.com/philipperemy/fractional-differentiation-time-series/blob/master/fracdiff/fracdiff.py
viz.
def get_weight_ffd(d, thres, lim):
w, k = [1.], 1
ctr = 0
while True:
w_ = -w[-1] / k * (d - k + 1)
if abs(w_) < thres:
break
w.append(w_)
k += 1
ctr += 1
if ctr == lim - 1:
break
w = np.array(w[::-1]).reshape(-1, 1)
return w
It’s like a fir filter Implement the kernel and run, nothing more nothing less