Calendar metrics#
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sigtech.framework.analytics.performance.performance_calendars.get_presentation_performance_table(ts, use_ir_calc=False, method: str = 'compounding', scaling_units=1)
Calculate the combined performance calendar and annual statistics DataFrame.
- Parameters:
ts – Input timeseries.
use_ir_calc – Use risk Sharpe calculation (default is False).
method –
'arithmetic'or'compounding', aggregation method (default is'compounding').scaling_units – value to divide timeseries by (default is 1).
- Returns:
Combined performance calendar and annual statistics DataFrame.
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sigtech.framework.analytics.performance.performance_calendars.performance_calendar(rets: Series, geometric: bool = True, method: str = 'compounding') DataFrame
Calculate the performance calendar.
- Parameters:
rets – Daily returns.
geometric – If True, compute the geometric returns (default is True).
method –
'arithmetic'or'compounding', aggregation method (default is'compounding').
- Returns:
DataFrame of monthly returns.
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sigtech.framework.analytics.performance.performance_calendars.rolling_risk_sharpe(ts, period=252)
Calculate the rolling risk Sharpe using the risk day count factors.
- Parameters:
ts – Input timeseries.
period – Input period (default is 252).
- Returns:
Rolling risk Sharpe.
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sigtech.framework.analytics.performance.performance_calendars.rolling_risk_volatility(ts, period=252)
Calculate the rolling risk volatility annualised using the risk business day count.
- Parameters:
ts – Input timeseries.
period – Input period (default is 252).
- Returns:
Rolling risk volatility.