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Is it possible to perform backtesting in a notebook environment (or local linux env) for programmatic access to the result metrics (eg. PSR) ?
When developing a python strategy, is it possible to debug / test using small data slices outside of scheduling a full backtest of the main.py strategy?
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Hi Ryan Bell ,
It is not possible to perform a full backtest in a notebook.
The PSR is not available at the "algorithm level", it belongs to the "engine level" in the result handler. After we run the backtest, its final value and a rolling window are available in the results json file.
What is the objective of testing using a small data slice? If we know that we give a concrete answer.
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Ryan Bell
Got it. I think with a little bit of abstraction, I could experiment in a local Backtrader environment with a SharpeRatio then port to QuantConnect.
The research notebook is great, but without being able to run an algorithm or simulate scheduled events, it's utility for prototyping is limited.
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