Diagnosing a Missing Buy Signal Column in a Backtest

Summary

This forum post describes a BigQuant backtest that raises a pandas KeyError for the column named buy_signal. The strategy code queries daily stock data and creates a factor field, then the trading handler filters context data using buy_signal equal to one. The query shown does not create a column with that name, so the failure points to a mismatch between the fields supplied to the backtest and the field the handler expects.

The post provides the code and traceback but no reply or confirmed fix. A practical debugging step is to inspect the actual columns in the data passed to the engine and ensure the signal column is explicitly created or change the handler to use a field that exists. The factor expression itself is not shown to be the source of this exception. This is a narrow implementation example, not evidence about whether the proposed stock selection logic is profitable or robust.

Key ideas

• The traceback indicates that the backtest handler requests a column absent from its data.
• The shown query creates a factor field but does not visibly create the expected buy signal field.
• Inspecting the input data columns can distinguish a naming mismatch from a factor calculation problem.
• The post does not include a verified correction or any strategy performance evidence.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.