Hi QC Community,

As Mercedes-Benz would say, some things are too good to not share. So here (attached) is a ML Crypto Algo template for you to add to your quant research tools. It was built with a lot of help from QC Support so everyone should benefit. (Thanks Louis Szeto, Varad Kabade & Vladimir). This is a very instructive all-in-one ML template on 1) how to structure your code to initialize & handle rolling windows and indicators in the QC Algorithm Framework, 2) how to add Indicators from the QC indicator suite, 3) creating indicators from indicators, 4) creating a dataframe for your feature set from the ‘rolling windows of’ indicators, and 5) preparing your feature dataset to pass to the Machine Learning model. 

This example uses ‘BTCUSD’ crypto, but really, that can be easily switched out in order to experiment with any asset type. It is set up also in general to emit both long and short signals / insights, even though the Bitcoin cash market cannot be shorted. You can also easily plug in and try any of your favorite Machine Learning models (Neural Network, Ridge Classifier, SVC, Random Forest, XGBoost, etc). Enjoy and feel free to post your enhancements!