Grouping Stock Price-to-Earnings Ratios by Industry
Summary
This short forum answer addresses how to aggregate price-to-earnings data across stocks in an industry. It suggests using a grouped sum operation keyed by an industry classification and applying it to trailing-twelve-month P/E values in a stock-factor dataset, with a query filtered by date. The approach is intended to produce a date- and instrument-level result alongside the industry field and grouped value.
The example is a platform-specific implementation hint, not a complete definition of sector valuation. Summing constituent P/E ratios does not generally produce a meaningful aggregate industry P/E: a more interpretable sector multiple is typically calculated from aggregate market capitalization divided by aggregate earnings, with explicit handling for loss-making firms and missing data. The post does not discuss weighting, negative earnings, survivorship, or validation, so its aggregation should be checked against the intended research question.
Key ideas
- The answer uses an industry grouping field to aggregate constituent stock P/E values by date.
- It demonstrates a grouped-sum operation over trailing-twelve-month P/E data.
- A sum of constituent P/E ratios is not generally equivalent to an industry-level P/E multiple.
- A sector multiple should define its aggregation method and treatment of loss-making or missing observations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.