What is point-in-time data, and why does it matter?
Reviewed against the platform's code on Sep 23, 2026
Point-in-time data records each value as it was known on each date — when a filing was published, before later restatements, including companies that later disappeared — so that a test of a past decision uses only the information that decision could actually have used.
Why it matters
Using today's revised numbers, or only today's surviving companies, to test past decisions leaks the future into the past. Lookahead and survivorship bias make backtests look better than any real investor could have done.
How it works
Point-in-time datasets keep the publication date of every value and the history of revisions, keep delisted securities, and lag economic series by their real release delay before they may enter a day's observation.
How Opulence Alpha applies it
Opulence Alpha reads fundamentals as of their filing dates, records what could not be measured as unmeasured rather than zero, and places economic releases on the day they were published before the regime engine may use them.
Sector behaviour by regime, measured without look-ahead →Related concepts
Questions
- What is lookahead bias?
- Using information in a backtest that was not yet available at the time of the simulated decision — for example, revised earnings or a later release date.
- What is survivorship bias?
- Testing only on companies that still exist today, which removes the failures and flatters past returns.
- Why lag economic data?
- Because figures such as GDP or CPI are published weeks after the period they describe; a model may only use them from the publication date.
Educational content about research methods. Not investment advice.