Analyzers stats when datas have only trading days

exu

Hi there,
I'd like to know if the fact that a line has only trading days (i.e 180 days instead of 365) in a year, could affect analyzers calculations such as annualized returns, because something like that would be wrong:

dt = st.data._dataname['open'].index
bt_period = dt[-1] - dt[0]
bt_period_days = bt_period.days
annual_return_pct = (1 + total_return)**(365.25 / bt_period_days) - 100)

ab_trader

I've used different sources of data for stocks and futures, but never seen weekends or holidays included in the data sets. I assume that the standard approach is to skip empty days and keep only trading days.

bt uses standard number of days (252) for the annualization.

exu

@ab_trader :
Thanks, yes of course. The example above came from this guy's performance report:
https://github.com/Oxylo/btreport/blob/master/report.py and it relies on ALL the days of the period, just checking on how the built-in analyzers deal with that...

ab_trader

@exu

The calculations above looks correct. Doesn't matter how many trading days you have, dt[-1] - dt[0] will give you calendar number of days.

backtrader

@exu said in Analyzers stats when datas have only trading days:

just checking on how the built-in analyzers deal with that...

I fail to understand what the built-in analyzers have to deal with. They have de-facto default values (the ones mostly used by the industry/people/call-it-X) which you can customize to your liking.