BT Portfolio Backtest
BT Portfolio Backtest: BT Portfolio Backtest: specialized toolkit for 3+ finance workflows covered in the triggers section.
Overview
Constraints
Evidence Quality
Medium confidence — review before critical use
34 non-negotiable constraints
WHENWhen implementing data input for backtesting
ACTIONverify the price DataFrame index is a DateTimeIndex for time-series alignment
CONSEQUENCEWithout a DateTimeIndex, pandas datetime operations like shift() and offset calculations will fail or produce incorrect results, corrupting backtest calculations
WHENWhen passing price data with duplicate column names
ACTIONallow duplicate column names in the price DataFrame
CONSEQUENCEDuplicate columns cause ambiguous column access and can lead to incorrect signal generation or position sizing based on wrong securities
WHENWhen providing price data to Backtest
ACTIONuse a datetime-indexed pandas DataFrame or Series as the data source
CONSEQUENCENon-datetime indexed data causes pandas datetime operations to fail, preventing proper time-series alignment and offset calculations
FAQ
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Changelog
v0.1.0: Initial release on Doramagic.ai. Auto-generated batch-v1 metadata and FAQs based on zvtvz/zvt.