Comments (4)
I also changed to use https://github.com/Lumiwealth/quantstats_lumi
No all problems i had with the original library are fixed, check it out.
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Try this:
qs.reports.html(returns_df.sharpe, "SPY", rf=0.000066, output = "..path../Strategy Tearsheets/strategy_report.html", compunded=False)
Note also that some others are now maintaining @ https://github.com/Lumiwealth/quantstats_lumi
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Thank you @DannyMartens - the compound = False has not changed much.
I have also tried installing quantstats_lumi as well and I am comparing the results with quantstats.
I can see for now that Lumi overestimates (circa 10%) the Sharpe Ratio of the other library quantstats - anyway I seem to understand the Lumi version is better maintained? Anyway, this difference does not bother me too much
Can you please let me know what is the right way of entering the Risk Free value in the report.html?
If we have a US 10 yrs at 4.61% as of now, in the html.report function I am using the Avg RF Daily Returns which according to my calculations (for my time window of observation) would be 0.000066, so I am entering 0.000066 as below:
qs.reports.html(returns_df.sharpe, "SPY", rf=0.000066, output = "/Users/.../Strategy Tearsheets/strategy_report.html")
Is this the right way to use RF rate here?
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Related Issues (20)
- Plots don't display when using matplotlib backend qt HOT 1
- Is this project **ABANDONED** ? HOT 1
- Asset Wise Transaction List - Profit Loss Account
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- Warings about pd.to_timedelta
- 'TypeError: super(type, obj): obj must be an instance or subtype of type' in the super() function of reports.html HOT 1
- stats.py: res = abs(total + 1.0) ** (1.0 / years) - 1 <-- ZeroDivisionErrorZeroDivisionError HOT 1
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- Calculation of 3Y and 5Y annualized return date lag
- report.py's cagr function doesn't include the days per year options HOT 1
- Fix kelly_criterion formula for investment scenario
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