Glad to see that Quantconnect seems to be agile and willing to update methods for their algo selection. I also find it comforting that Lean is opensource, so I can check the implementation and their test cases. :)
For those that want to do some quick and dirty backtest or optimization/investigation in research, please do keep in mind the inevitable computation differences between LEAN and simple PSR computation in notebook. I think this is one of those little but important things most engineers/data scientists have to deal with when working among different environments. Anyways... per Alexandra's response, "rolling PSR" is computed by LEAN (I can't seem to figure out where the rolling part is though in github), while Jack's PSR is a single value derived from one stream of returns. Below shows you the difference for Sharpe Ratio (SR) and PSR for a few tickers if you buy-and-hold in the same timeframe between notebook (using annualized SR) and Lean. I would expect PSR for SPY to be a bit closer to 50% from LEAN. Avid notebook users... beware!
SPY
notebook SR: 0.836, PSR: 50.000%
Lean SR: 0.900, PSR: 41.185%
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SHY
notebook SR: 1.237, PSR: 68.901%
Lean SR: 1.224, PSR: 69.799%
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QQQ
notebook SR: 0.910, PSR: 52.476%
Lean SR: 0.990, PSR: 49.063%
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AMZN
notebook SR: 1.218, PSR: 83.669%
Lean SR: 1.339, PSR: 78.661%
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GE
notebook SR: -0.458, PSR: 10.897%
Lean SR: -0.306, PSR: 0.159%
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