Finding the Row-Wise Minimum Across Five Price Series

Summary

The document answers a question about selecting the lowest closing price across five days for a market risk-control calculation. It explains that applying Python's built-in minimum directly to several pandas Series can be ambiguous: the intended comparison may be across the five values at each row, rather than across entire Series. The proposed method is to combine the Series as columns in a DataFrame and calculate the minimum along the column axis, producing a row-wise minimum.

This is a compact data-handling tip relevant to preparing price features for a trading or risk workflow. It addresses the shape and direction of a comparison, rather than proposing a risk rule or validating the resulting measure. The document does not specify missing-value handling, date alignment among the Series, or downstream use of the five-day low, so those details would still need to be considered in an implementation.

Key ideas

• Combine the five price Series as columns in a DataFrame before comparing values row by row.
• A minimum across columns yields the lowest of the five values for each row.
• The axis setting determines whether the calculation is horizontal across columns or vertical down rows.
• The example does not discuss date alignment or missing-value treatment.

Tags

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