Live tools - analyze it yourself

MFPRO is the flagship app for comparing and analyzing funds. The MF Processor is the companion for pulling a specific fund’s holdings composition.

• MFPRO - Mutual Fund AnalyticsCompare up to 200 funds side by side. Returns, risk metrics (Sharpe, Sortino, Treynor, alpha, beta, max drawdown, capture ratios), multi-period rolling returns with custom evaluation windows, SIP returns, and category-level benchmarking against Nifty and other indices. Also shows holdings composition for a curated set of funds.
• MF Portfolio Files ProcessorNeed the composition of a specific fund that is not in MFPRO’s composition set? This AI tool reads a fund’s monthly portfolio disclosure and extracts clean holdings data with automatic schema detection.

What is new

Recent releases and guides on the MFPRO tool and the NAV data, newest first.

• SIF had its biggest month yet: net assets Rs 31,175 croreSep 2026. Net inflows of Rs 7,699 crore in August and folios past 125,000. Equity Ex-Top 100 Long-Short grew about 66% and now spans seven fund houses.
• Heavy user of the NAV API? Run your own NAV service inside your own setupSep 2026. The 169 MB Parquet copy holds every scheme and every date back to 2006. DuckDB or Polars read it where it sits, with no database server to install.
• MF NAV in the wild: what the API logs show about how the data is pulledSep 2026. AI agents, Google Sheets and Apps Script, Excel and Power Query, an iPhone app, Zoho, n8n, plain Python, and DuckDB querying the Parquet in place.
• The API is not the only way in: download the NAV database from the appSep 2026. The full history since April 2006 as parquet, csv, tsv or SQLite, the 1.1 MB latest snapshot, or just the funds you pick.
• The whole NAV dataset as one file, with a manifest for cheap refreshesSep 2026. One Parquet holds every scheme and every date. Poll the small manifest, or send its ETag back for a free 304.
• SIF: every NAV AMFI has published for the new fund category, downloadableSep 2026. Specialized Investment Funds nearly doubled in three months. CSV and Parquet at sif.tigzig.com, refreshed twice a day.
• Three upgrades on the NAV API: gzip, CSV output, better bulk filesAug 2026. Aimed at Power Query, Excel WEBSERVICE and browser trackers.
• Composition analytics for 24 of the largest equity fundsAug 2026. Ten monthly snapshots, reconciled against the AMC printed totals. Compare a fund over time, against peers, or against a benchmark.

Returns metrics

How returns are measured, from the headline CAGR to the full rolling-return distribution. Each page has the formula, a worked example and interpretation.

• CAGR (Compound Annual Growth Rate)The annualized return that smooths a fund’s ups and downs into one number.
• Rolling ReturnsReturn for every possible holding period, not just one start date.
• Standard Deviation (Volatility)How spread out a fund’s returns are around the average.
• Maximum DrawdownThe worst peak-to-trough fall before a fund recovered.
• Calmar RatioReturn earned per unit of maximum drawdown pain.
• Beat RateThe share of rolling periods where a fund beat its benchmark.

Risk metrics

Market sensitivity, skill vs luck, and reward-per-unit-of-risk, all computed on daily NAV returns against a benchmark.

• Beta and R-SquaredA fund’s market sensitivity, and how much the market explains it.
• Alpha and t-statisticExcess return over the market, and whether it is statistically real.
• Sharpe RatioExcess return earned per unit of total volatility.
• Sortino RatioReturn per unit of downside risk, ignoring upside swings.
• Tracking Error and Information RatioHow far a fund strays from its benchmark, and whether the strays pay off.
• Capture Ratios (Upside and Downside)How much of the market’s rises and falls a fund captures.
• Win RateThe share of periods a fund finished in positive territory.

Advanced risk

Tail risk, distribution shape, drawdown pain and diversification, for a deeper read than the headline ratios.

• Treynor RatioExcess return per unit of market risk (beta).
• Value at Risk (VaR) and CVaRA loss threshold at a confidence level, and the average loss beyond it.
• Skewness and KurtosisThe asymmetry and fat tails of a fund’s return distribution.
• Ulcer IndexDrawdown pain measured by both depth and how long it lasts.
• Drawdown and RecoveryThe biggest falls, how deep they went, and how long they took to recover.
• Correlation MatrixHow closely funds move together, for diversification decisions.

Scoring & ranking

Turn many metrics into one comparable view: a custom weighted score and peer-set percentile ranks.

• Dynamic ScoringRank funds by a custom weighted blend of returns and risk metrics.
• Percentile RankWhere a fund sits within its peer set, metric by metric.

The data & API

What is actually in the NAV database, how it is built and validated, and how to pull it yourself. Free, no-auth access to the same AMFI NAV data the tools run on.

• MFPro NAV Master: Data DictionaryEvery field, what it means, what it covers, and where it is imperfect.
• How the Data Is BuiltThe sources, the refresh cadence, the backfill, the validation, and the limits.
• Scheme Universe Field GuideHow AMFI categories work, which fields to use, and the old-to-modern mapping.
• TXIC CodeA short, deterministic, human-readable identifier for every scheme.
• Composition ValidationThe cross-checks behind the holdings data, with the current pass and mismatch counts.
• MF NAV API - referenceQuery per-scheme NAV history or download the full dataset (CSV / Parquet / SQLite). No key, no sign-up.
• Free Mutual Fund NAV API for India (AMFI) - guideWhat the API returns, how to call it, and how the AMFI data is assembled.

Background reading

A couple of pieces worth reading alongside the metrics.

• Rolling Returns: Why CAGR Alone Can Mislead YouWhy a single start-date return can deceive, and what the rolling-return distribution shows instead.
• MFPRO v2 - rolling returns, custom eval periods, multi-period comparisonsRelease notes for the current MFPRO capabilities.