Mutual Fund & ETF Analyzer
Analyse an imported NAV series for CAGR, volatility, drawdown and risk-adjusted return with transparent assumptions.
How to use this Mutual Fund & ETF Analyzer
The analyzer converts a dated NAV series into a compact risk-return diagnostic. It is intentionally data-input driven: if a refreshed official series is not bundled, the user must import the observations instead of receiving an apparently current result from stale data. AMFI provides official NAV and fund-information resources that can support a governed production dataset.
Calculation logic
CAGR uses first NAV, last NAV and the exact date span. Periodic returns are calculated between consecutive positive NAV observations. Annualised volatility scales the sample standard deviation by the square root of the entered observations-per-year. Sharpe and Sortino now use periodic excess returns against a converted periodic risk-free assumption rather than subtracting the annual risk-free rate directly from CAGR and dividing by volatility. Maximum drawdown is measured from each running NAV peak.
Worked interpretation
Two funds can show the same five-year CAGR but very different drawdowns and periodic volatility. The analyzer helps expose that difference. For a production comparison, use a complete series with a recorded effective date and consistent frequency rather than a hand-picked set of NAV points.
What this result does not prove
Frequency matters. Daily, monthly and irregular observations cannot be mixed casually, and missing observations can distort volatility and downside metrics. Sharpe and Sortino are descriptive statistics, not forecasts. Comparing schemes also requires appropriate benchmark/category context, current TER, exit load and portfolio information; this page does not generate a 'best fund' recommendation.
Methodology, data and limitations
This Finin2min tool separates calculation from recommendation. Inputs, return assumptions and stress parameters remain visible and editable. Results are educational scenarios, not forecasts or suitability advice.
Primary / official references
- SEBI — Mutual Funds Regulations, 2026 (last amended 7 Jul 2026)
- SEBI — Master Circular for Mutual Funds, 20 Mar 2026
- SEBI — Circulars index (check post-Master-Circular updates)
- SEBI — Categorization and Rationalization of Mutual Fund Schemes, 26 Feb 2026
- AMFI — NAV Download
- AMFI — Total Expense Ratio
- AMFI — Portfolio Disclosure
Questions & answers
What does the Mutual Fund & ETF Analyzer calculate?
The analyzer converts a dated NAV series into a compact risk-return diagnostic. It is intentionally data-input driven: if a refreshed official series is not bundled, the user must import the observations instead of receiving an apparently current result from stale data. AMFI provides official NAV and fund-information resources that can support a governed production dataset.
What assumptions drive the result?
CAGR uses first NAV, last NAV and the exact date span. Periodic returns are calculated between consecutive positive NAV observations. Annualised volatility scales the sample standard deviation by the square root of the entered observations-per-year. Sharpe and Sortino now use periodic excess returns against a converted periodic risk-free assumption rather than subtracting the annual risk-free rate directly from CAGR and dividing by volatility. Maximum drawdown is measured from each running NAV peak.
Can I treat the result as a forecast or recommendation?
No. The output is an educational scenario generated from the values entered. It does not predict market returns, recommend a security or establish suitability for an individual investor.
How should I handle market or mutual-fund data?
Use a current, complete dataset with a recorded effective date. Where the page requires imported scheme, NAV, TER, portfolio or industry data, Finin2min should publish or retain the source authority, retrieval date, parser version and file hash.
What are the main limitations?
Frequency matters. Daily, monthly and irregular observations cannot be mixed casually, and missing observations can distort volatility and downside metrics. Sharpe and Sortino are descriptive statistics, not forecasts. Comparing schemes also requires appropriate benchmark/category context, current TER, exit load and portfolio information; this page does not generate a 'best fund' recommendation.