Hello

The network Deep Q which is based on re-enforcement learning , the algorithm would continue learn on-line until results cannot be improved,

The result of the network learning would be transferred  to MT,

The idea using a Node.js app,  is to use data from MT (OHLC and indicator data ) to feed  Deep Q Nework as input

The deep Q network wo…[Read more]

I have chosen to implement version shown in http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html

Although  you research and write your own version by studying white paper at http://arxiv.org/pdf/1312.5602v1.pdf

The code is written in JavaScript so it can be ran in your browser, my suggestion if you want to run it locally then si…[Read more]

Hello

If you would like further information on the source code and operation, theory  you can check http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html

1)The first step has already been taken into add raw Forex data  to network

2) Add further inputs such as simply indicators

3) Build Node.js App  to integrate to metatrader 4…[Read more]

Hello Group

The bottom line is find an edge, in future I’ll add basic indicators such as moving average, bands or RSI as an input then monitor results

Also it possible to add close prices inter-market related data

The demo at https://youtu.be/QJHpaIZ7o_c  is based on 5 minutes raw price data nothing else , and it attempting to place 1)Buy Exi…[Read more]

Interesting vid! The ‘Theory of Everything’, and physical Unified Field Theory being only a part of it ? Wow – this guy has really got a vision! And all this uncovered by AI algorithms. Forgive me if I’m a bit doubtful about this.
<b><i><u>Google brought his company for $400 Million, maybe the saw something of interest.</u></i></b>

Back to our…[Read more]