How we measure /
what we measure with.
Every formula, every methodology, every assumption — written down. Every metric on MintByte traces back to a documented page here: the source-of-truth, the equation, the edge-case behaviour, the date we last reviewed it.
Numbers without methodology are just opinions in monospace.
The mutual-fund industry has spent twenty years training Indian investors to compare 5Y CAGR numbers without ever knowing whether two funds compute their CAGR the same way. They usually don't. SIP vs lumpsum CAGR, dividend reinvestment treatment, NAV cut-off dates — every step has a choice, every choice changes the answer.
The methodology pages here state the choice. Every number that appears on any MintByte page is computed by code that's version-controlled and reviewable. The pages below are the English-language explanation of that code.
Risk metrics
7 pagesHow we measure the bad side of returns — volatility, drawdowns, and downside-weighted ratios.
Sharpe ratio
Risk-adjusted return that shows how much excess return a fund earns per unit of total volatility.
Sortino ratio
Risk-adjusted return that penalises only downside volatility, making it more suitable than Sharpe for skewed equity funds.
Volatility
Standard deviation of a fund's returns, annualised — the most widely used measure of total return dispersion and investor discomfort.
Downside deviation
Standard deviation computed using only the months where returns fell below a target — isolating the risk that actually hurts investors.
Drawdowns
Peak-to-trough NAV decline that measures how far a fund fell from its high before recovering.
Max drawdown
The single largest peak-to-trough NAV decline over the look-back — a one-number summary of a fund's worst historical loss.
Recovery period
The number of months a fund took to climb from its maximum drawdown trough back to the prior peak NAV.
Return calculation
3 pagesEvery formula we use to turn NAV series into the return numbers displayed on fund pages.
How we compute returns
Every return number on MintByte traces to one of three formulae. Here are the formulae, the data window, and the rounding rules.
Rolling returns
Returns computed over every possible overlapping window of a fixed length, removing start-date and end-date bias from performance assessment.
Tracking error
Standard deviation of a fund's return minus its benchmark's return — measures how precisely an index fund replicates its benchmark.
Market risk & factor exposure
5 pagesHow we decompose a fund's return into benchmark-linked and manager-driven components.
Alpha and beta
Jensen's alpha quantifies manager skill as excess return above CAPM prediction; beta measures a fund's sensitivity to benchmark moves via covariance/variance.
Alpha
A fund's return in excess of what its beta-adjusted market exposure would predict — the measure of active management skill.
Beta
Measures how sensitive a fund's returns are to benchmark movements — a β > 1 amplifies market swings, β < 1 dampens them.
Capture ratios
Up-capture and down-capture measure how much of the benchmark's gains a fund captures vs. how much of its losses it absorbs.
Factor exposure
Decomposition of a fund's returns into systematic risk factors — size, value, momentum, quality, and low-volatility — to explain the source of alpha.
Categorisation & ranking
3 pagesHow funds earn stars, quartiles, and peer-percentile positions on MintByte.
5-star rating
How MintByte assigns 1–5 stars to mutual fund schemes — a composite quintile rank across risk-adjusted return, consistency, expense efficiency, and AUM stability.
Quartile rank
A fund's position within its peer category divided into four equal buckets — Quartile 1 is the top 25%, Quartile 4 is the bottom 25%.
Peer percentile
A fund's exact position in its category as a continuous 0–100 score — 95th percentile means the fund outperformed 95% of peers.
Cost & AUM dynamics
3 pagesThe compounding drag of fees and the capacity limits that erode alpha at scale.
Expense ratio drag
How Total Expense Ratio compounds against corpus growth over time — a small annual fee becomes a large wealth transfer over decades.
TER drag
Alias for expense ratio drag — the compounding wealth cost of a fund's Total Expense Ratio over an investment horizon.
AUM decay
The empirical pattern where funds with very large AUM find it increasingly hard to generate alpha, as large positions create market impact and limit nimble stock selection.
Institutional signals
1 pagesIndicators derived from mandatory shareholding disclosures and institutional flow data.
Methodology is reviewed for accuracy every six months at minimum, and more frequently when underlying regulations change. MintByte is an AMFI-registered mutual fund distributor (ARN-314872); SEBI Registered Research Analyst (APRN-01658). Not investment advice.