Using a simple machine learning model with a Logistic Regression model to predict and trade currencies. Currently it is on fixed/static time prediction (next bar), improvements will be used for varying forward time window prediction(Instead of using 5 min bars to predict the next 5 mins, aim to predict longer ahead)
Another interesting idea is trying to predict over an amount (basically transaction costs). Will aim to bin the data after minusing the transaction costs.
Example: https://github.com/SolbiatiAlessandro/RNN-stocks-prediction (dynamic prediction).
Also will aim to look at or account for variable change in prediction, say you in are currently in a trade but new data (or news) comes in suggesting that the current prediction is no longer accurate (try to minimise position or close out the current position).
Live trading is being implemented and working rudementary (trade at your own risk)
Documentation for FXCM API: http://fxcmpy.tpq.io/
Adpated from and credits go to : http://hilpisch.com/fxcm_ai.html
Download or install jupyter notebook to view files
Add your token from FXCM to the fxcm.cfg to start trading (Create a demo account and login to https://tradingstation.fxcm.com/ and find the token (should be under account)
Unique implimentation of this is binning the data according to voltility
