Quote:
Originally Posted by DeltaLover
The biggest challenge lies in the way your training data are presented in your earning algorithm. Of course the data transformation can also require ML so we can say that the process is recursive to some extend. The size of your training universe is proportional to the features you are going to pass as the deepness of your networks as well.
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Absolutely. If one is using standard PP data, finding stuff that everyone else misses or overlooks is almost impossible. Whatever one discovers is guaranteed to be found (or to have been found) by others.
One of the "depth" problems is that the more factors/attributes included, the more likely it is that others will be using the same factors/attributes (more or less in combination with other factors/attributes that one may or may not be using). It often seems that trying to include too many factors is a bigger problem than including too few. Fewer factors, better prices.