How do I analyze custom data (lets say a csv file based on earning reports or some other events) using python (pandas/numpy) and generate buy/sell signals and backtest ?
A. Can I analyse the data in quantconnect so I don't have to uplaoda csv file and it could work in real time
B. If I analyse the data outside (lets say google colab), generate a CSV file with buy and sell indicator. Now can I upload to quantconnect and backtest it?
This is not the strategy I am considering but just to give an idea lets say I have earning report from some source which I downlaoded (or used api) and processed with python/pandas (on google colab or quantconnect) and created a csv like this.
Date Symbol EPS. Rating. Buy_indicator. Sell_indicator. Position
2020-1-1 APPL 23 Good. 1 0 1
2020-1-2 GOOG 12 Good 1 0 1
2020-04-1 APPL 30 Good 1 0 2
2020-04-2 GOOG 11 Bad 0 1 1
2020-07-1 APPL 25 Neutral 0 0 2
2020-07-2 GOOG 10 Bad 0 0 0
Now I want to the load the above csv data (if not created within quantconnect) in Quantconnect and backtest the strategy using buy/sell/positon indicators.