Public, regulator- and exchange-sourced data - not a proprietary panel or third-party data vendor. Refreshed nightly through an automated pipeline.

AMFI - mutual fund data

The Association of Mutual Funds in India publishes daily NAVs and monthly scheme-level portfolio disclosures for every AMFI-registered mutual fund. This is the source for scheme metadata, NAV history, portfolio holdings (used in our fund overlap and portfolio X-ray tools), TER, dividend/IDCW payouts, and fund manager attribution.

Mutual fund NAV history is backfilled from 2010 onward. Coverage spans every AMFI-registered scheme across all categories (equity, debt, hybrid, and more) - 8,600+actively tracked schemes, plus retained history for older, wound-up, or merged schemes rather than dropping them once inactive.

NSE - stock and index data

The National Stock Exchange is the source for stock prices, fundamentals, corporate actions, and shareholding data for around 1,400+ liquid, AMFI-relevant names - broadly the most liquid, AMFI-relevant universe rather than every micro-cap name on the exchange.

Key NSE benchmarks (Nifty 50, 100, 200, 500, Midcap 50/100, Next 50, Smallcap 100, and their TRI variants) run from January 2004, with price-return versions from January 2005.

BSE - index data

BSE indices (Sensex, 100, 200, 500, and TRI variants) run from January 2006, used alongside NSE benchmarks for context and cross-checking.

Global indices, for context

S&P 500, Nasdaq, MSCI ACWI, and MSCI Emerging Markets are tracked from January 2010, MSCI World from January 2012 - used for global context, not as a primary data source for Indian fund/stock analysis.

DEPTH VARIES BY FIELDSome fields - like detailed portfolio holdings or specific factsheet metrics (duration, turnover) - have shorter or partial history because they depend on when regulators and AMCs began disclosing them, not on a limitation in our pipeline. Around 700+ benchmark and reference indices are tracked daily in total, domestic and global.

How freshness and accuracy are handled

Data is ingested and enriched nightly through an automated pipeline, with every job run tracked for completion and failure so gaps get caught rather than silently persisting. When ingestion gaps are found - for example, a stock-data filter that was silently excluding certain trading-segment records - they get fixed and the affected history backfilled. Coverage isn't uniform across every field; we'd rather say that plainly than imply completeness that isn't there yet.