They claim that their Pipelined Recurrent Neural Network performs better than the the human brain recognizing sequential signal patterns such as stock prices.
Of course the beginning of 2000 that was the explositon of the idea that Artificial Learning algorythms are the holy grail. There are many commercial and free softwares available. Of course the obvious idea is to have a model for yourself. By now this is accessible to everybody, you can download and test arryex things or you cand download and test the Back Propagation Neural Networ (BPNN) with a whole library of inputs (SSA Caterpilar, Hodrick- Preskott, Jurik type of digital filtering, Volume Weighted Average Price VWAP, etc. etc.). However you will not get any edge.
The think is and there is the second part of the article.
whereas the human brain is better at recognizing "parallel signal patterns"—the human eye can easily tell a picture of a tiger from a picture of a cat.
And that I think is important. And that is why I try to make use of human pattern recognition tools that would be able to add an edge in Neural Net applications for trading purpouses. The first approach is the Elliotware but I also try another approaches as the Market State Analysis.
Using neural net models newbies should be very carefull. It may be boring but I have to say. Look at your fundamental calendar, do not be surprised, the market orders accumulation is also not accounted in the pattersn on which is trained the neural net. And there are so many things that are not in the model, so do not expect much from it.
It performs well when it is trained on the current market activity and you expect a microstructure event (I do not expect any neural net to predict a major top and bottom) provided nothing serious is happening right now. Just make sure of that.
I really liked too much a phrase from quantin123 it is not necessarily a joke:
Always keep in mind that NN is just a dumb calculator.
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