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Annual dataset

Indian Listed Companies Dataset Guide

A reproducible specification for company identity, exchange listings, symbols, ISINs, status, and annual snapshots.

Data and screening
AuthorRusaka Markets Research
Methodology reviewRusaka Markets Methodology Review
Last reviewed28/7/2026
Source coverage3 official references

What this resource does

A company dataset must distinguish the legal company, security, listing, symbol, exchange, and time period. Treating a symbol as permanent identity causes errors after renames, mergers, relistings, and exchange differences.

The annual snapshot records source, retrieval time, active status, security identifiers, and normalization decisions. Corrections create a new version rather than silently rewriting prior research.

Methodology

  1. Create stable company and security keys independent of display names.
  2. Store exchange, symbol, ISIN, series, listing status, and effective dates.
  3. Reconcile duplicates and conflicting sources with an evidence trail.
  4. Publish schema, coverage, exclusions, checksum, and snapshot date.

How to interpret it

A row count is not equivalent to the number of operating companies because one company may have several securities or exchange listings.

Annual snapshots support reproducible research, while current-state tables support discovery. Both are necessary and should not be substituted for each other.

Limitations and failure modes

  • Corporate actions can change identity relationships between snapshots.
  • Exchange coverage may be temporarily incomplete.
  • Delisted and suspended states require effective dates.
  • Dataset presence does not establish investment eligibility or liquidity.

Research workflow

  1. Ingest primary exchange identities.
  2. Normalize without discarding originals.
  3. Run duplicate and coverage checks.
  4. Version and document the snapshot.

Questions and answers

Why retain old symbols?

Aliases preserve links from historical filings and research while the canonical security identity remains stable.

Is the dataset a recommendation universe?

No. It is an identity and coverage resource. Suitability, liquidity, risk, and access require separate evaluation.