Learn Research data
Inspect availability timestamps, price and dividend conventions, and the identity of preserved research inputs.
What you will learn
A historical date does not prove historical availability. Distinguish observation dates, disclosures, revisions and universe membership. File reproducibility and point-in-time validity require different checks.
Follow the sequence below from definitions to input checks and public lessons. Distinguish numerical illustrations from actual run results.
Availability and population
What is point-in-time data? Understanding historical availabilityDistinguish observation dates, publication times and revisions, and understand why frozen data is not necessarily point-in-time data.What is lookahead bias? Using information that was not yet knownLearn how lookahead bias arises from information timing and the misuse of future evaluation labels.What is survivorship bias? The problem with today’s stock listUse fictional securities to examine the difference between survivors and the historical universe.J-Quants and Point-in-Time ResearchPoint-in-time research checks whether every input was available by the corresponding decision cutoff.
Prices and disclosures
Price return and total return: check the benchmark basisUse a fictional dividend example to distinguish price return from total return.J-Quants Adjusted Prices and Stock SplitsIn a fictional two-for-one split, a price moving from 2,000 to 1,000 alongside doubled shares does not itself imply a halving of holding value.J-Quants Financial Data: Periods and UnitsFinancial data has a reporting period and a disclosure timeline.J-Quants Disclosures: Times and Financial RevisionsA reporting period ends before its results are published.J-Quants Listed Issues and Market SegmentsA security master changes with listings, delistings and classifications.
Preserve inputs
What to check first in J-Quants price dataInspect existing local price data for dates, price conventions, duplicates, trading halts and freeze records.J-Quants Data Storage and Reproducible ResearchReproduction requires matching input content, selection rules, transformations and software versions.Reproduce a Study: Preserve Data, Settings and Run EvidenceBuild a reviewable evidence package linking input identity, recipes, software and receipts.
Explore connected topics
Applies to: main source candidate (unpublished) · Public source docs/en_US/GUI_RESEARCH_COURSES.md
Reviewed · KabuForge