I have coded a machine learning algo (sklearn) in Python, that uses different 'look back periods' for training a model, which is then used to predict future prices of a stock.
It has a 52% accuracy in predicting the future price. I now wish to build a simple strategy around this for backtesting. I am specifically interested in applying risk management, stoplosses, etc to test over a number of years.
Can anyone recommend a suitable Python-based backtesting platform for use with a sklearn ML algo that for each period looks back ata number of prior periods prices, trains a model, predicts future direction, and then issues orders to the backtesting platform?
Google has returned a whole range of options and so I am really after advice from anyone else that might have backtested a sklearn ML algo using a Python-based backtesting platform for recommendations...
Failing this, i might build a simple version myself.