A value strategy that ranks stocks using today's restated accounts may appear to predict yesterday's returns. Point-in-time data reconstructs what a specified research process could know at each historical decision. This lesson turns the hypothesis contract into rules for record versions, universe membership, transformations and reproducible snapshots.
Learning objectives. By the end of this note you should be able to:
- select the latest eligible version of a record at a historical decision;
- distinguish effective dates from availability dates;
- specify a point-in-time join and its missing-data policy;
- audit historical universes and feature transformations;
- design a truncation check for future-information contamination.
In this lesson
- The revised earnings example
- A minimal dataset contract
- Implement the version rule visibly
- Transformations can leak even when rows do not
- Audit with invariants
- From dataset to research evidence
Before you start
The full lesson, with worked examples and exercise solutions, is for members.
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