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Are you running your system across a range of Stocks?

Much appreciated. Summary data saves a lot of time...

Ah, I think the fact they are trying to sell it puts me off...

@conduit I know how you feel! But if we develop a thick skin, and stay focused on subject, I would really value your continued input...

Rohan, thank you for this most interesting post. What was name of the group with 70% accuracy please.

@conduit Running trials is a reasonable way to workout what structure surrounding the NN works well. However, for selecting (which I would rather not!) inputs it is less efficient as the range of potential inputs is vast. If you have any tips that might help me narrow that part of my efforts...

Indeed. I have some experience of model trading, but usually using statistical or heuristic rules. This is my first real foray into using a NN. I am using a library for the NN engine, but the design of input, structure and goals is mine. I am now at a stage where I can "test" these things by...

Glad you mentioned AlphaGo. That project was one of the reasons I am currently looking at deep learning for trading. You seem to have taken the approach I am interested in - using the NN to determine/define the inputs that add value to a strategy. Would you say that the way you have developed...

Thanks for this Dmitry. Very interesting paper. One point that intrigues me that is NOT covered in the paper is whether inputs needs to be correlated to the desired output. The paper suggests they do, but I wonder if two inputs (each uncorrelated to output) could not somehow add value when...

The neural net library I am using randomly sets the weights at the start of each "set" of iterations. If I do 10 set of iterations (all starting with different random weights). Is it "good" to average all weights before a prediction? Or should I just average the top 3?

Thanks! - That will have to be my bedtime reading tonight...

Hey Conduit, Perhaps I expressed myself poorly. What I was suggesting is that it would be nice/better if I could automatically select the inputs used, as opposed to selecting them myself. Might be more rigorous, and also bring in some previously (for me) unused inputs that I did not consider...

Excellent. I am an FX guy too. Using pure NN seems quite interesting, what I don't like is that I am having to select which inputs are used. This means I might be missing some important, but not obvious drivers.

Dmitry, do you show VAMI or equity curves for individual stocks anywhere?

I am working with some daily FX data. I have created 5 inputs: deltas, averages, RSIs etc. And I am trying to predict the "Forward" delta i.e. the price change 1,5 or 20 days ahead. I have normalised all data between the min and max of a fixed period and mapped that to range 0-1. I am looking...

Hey Conduit, are able to say whether you approach works on FX? I am from FX background, but I have data for FX and Equities.

Actually I found the issue. I had my input as 5 days delta, but output was 5 day delta OFFSET by 1. Since I corrected it, the NN now very closely matches solution to output as I was expecting. The reason for doing this (seemingly silly) test of same inputs as outputs was to CHECK that NN...

As you can see - the correlation (not surprisingly) is 1...

Activation is bipolarSigmoid. I am using 3500 days worth of daily FX data. And I am not sure what you mean by "what type of neuron"..

Surgo, I have 1 input neuron, 1 hidden layer with 1 neuron, and 1 output neuron. I am using the AForge library.