Mutual Fund Returns

CAGR, XIRR & Rolling Returns — Which Number Should You Trust?

A complete framework for reading mutual fund performance metrics, with a live case study on Nippon India Large Cap Fund.

Visiting Professor in Finance May 2026 Indian Mutual Funds
Introduction

Three metrics. Three different truths.

Every mutual fund advertisement quotes a return number. But which return? Calculated how? From which date? Most retail investors — and even many advisors — use CAGR, XIRR and rolling returns interchangeably, not realising that each metric answers a fundamentally different question.

Using the wrong metric can mean the difference between an apparently stellar 24% return and a sobering 6% — for the exact same fund, the exact same exit date, just a different entry point.

This report explains each metric clearly, demonstrates the pitfalls with real data, and gives you a decision framework for when to use which number.

CAGR

The smoothed annualised growth rate from a single start date to a single end date. Ideal for lump sum investments. Hides all volatility and path dependency.

Use when: Evaluating a single lump sum investment with a known entry and exit date.

Rolling Returns

Not a single number — a distribution of outcomes across all possible entry points for a given holding period. Reveals consistency, not just average performance.

Use when: Selecting funds, comparing fund managers, or stress-testing performance across market cycles.
Part 01 — CAGR

Compound Annual Growth Rate

CAGR represents the smoothed rate at which an investment would have grown if it had compounded at a constant rate every year. It assumes a lump sum invested on Day 1 and withdrawn on the last day, ignoring everything in between.

CAGR = (End Value ÷ Start Value)^(1 ÷ Years) − 1

Example

You invest ₹1,00,000 in a fund on 1 January 2019. On 1 January 2024, the corpus is ₹1,76,234. That is a 5-year CAGR of exactly 12% — regardless of whether the fund went up steadily or crashed 40% in 2020 and recovered sharply.

Invested
₹1L
Jan 2019, lump sum
End value
₹1.76L
Jan 2024
CAGR
12.0%
5 years
Wealth created
₹76K
Absolute gain

"CAGR is like a flight's average speed. If the journey took 5 hours at an 'average' 600 km/h, it doesn't tell you that the plane was grounded for two hours in Mumbai due to fog."

The start-date trap

CAGR's biggest vulnerability is that it can be manipulated simply by choosing a favourable start date. Two investors in the same fund will report wildly different CAGRs depending solely on their entry point. This is the mechanism behind most misleading mutual fund advertisements.

Watch out: When a fund advertises a CAGR figure, always ask "from which date?" A fund advertising 24% CAGR has almost certainly used March 2020 (the COVID bottom) as its start date. Shifting the start date by just 5 months can drop the CAGR by 3 to 5 percentage points.
Part 02 — XIRR

Extended Internal Rate of Return

XIRR is CAGR's smarter sibling. It handles multiple cash flows at different dates — exactly what happens in a Systematic Investment Plan (SIP), or when you make partial redemptions or top-up investments. XIRR solves for the single annualised discount rate that makes the Net Present Value of all dated cash flows equal to zero.

NPV = Σ [ Cash Flow(t) ÷ (1 + XIRR)^(t/365) ] = 0

Technically, XIRR is the solution to this equation, computed iteratively. Excel, Google Sheets, and every online SIP calculator solve it for you. But understanding what it represents is critical for correct interpretation.

Why XIRR > CAGR for SIP investors

Consider a ₹10,000/month SIP for 5 years. The first instalment compounds for 60 months; the last instalment barely compounds at all. CAGR on a "total invested" basis completely misrepresents this asymmetry. XIRR accounts for it precisely by tagging each cash flow to its exact date.

SEBI mandate: Since 2021, SEBI requires all mutual fund houses to disclose returns on SIP investments using XIRR, not simple CAGR. If a fund fact sheet uses CAGR for SIP returns, that is technically non-compliant with SEBI guidelines.

Key insight: rupee cost averaging lifts XIRR above lump sum CAGR

In a fund with significant volatility, the SIP investor's XIRR often exceeds the lump sum investor's CAGR. The reason: SIP investors automatically buy more units when the NAV is depressed (market crashes) and fewer when it is elevated. This rupee cost averaging effect is invisible in CAGR but fully captured in XIRR.

Part 03 — Rolling Returns

Rolling Returns

Rolling returns do not give you one number — they give you a distribution of outcomes. You choose a holding period (say, 3 years) and compute the CAGR for every possible 3-year window in the fund's history: Jan 2010 to Jan 2013, Feb 2010 to Feb 2013, and so on daily until the last possible window.

The result is hundreds or thousands of data points that collectively answer the question: "Across all market cycles, how has this fund performed for investors who stayed invested for 3 years?"

What it shows
Return distribution
Min, max, median, % positive
Best metric for
Fund selection
Comparing consistency
Bias eliminated
Recency bias
No cherry-picking possible

"A fund with an average 3-year rolling return of 12% and 96% positive windows is a fundamentally different proposition from a fund showing 15% trailing CAGR from a cherry-picked start date."

The key outputs from rolling return analysis are: the minimum return (worst case for a patient investor), the median return (typical experience), the percentage of windows with positive returns, and the beat rate against the benchmark. These four numbers tell you far more than any single CAGR.

Part 04 — Case Study

Nippon India Large Cap Fund — A Three-Lens Analysis

Launched on 8 August 2007, Nippon India Large Cap Fund is one of India's most tracked large-cap equity funds, benchmarked against the Nifty 100 TRI. It has grown from ₹8,676 crore AUM in March 2020 to over ₹51,690 crore by 2026, making it an ideal real-world specimen for this analysis.

Nippon India Large Cap Fund — Direct Plan (Growth)

Fund snapshot as of May 2026

Managed by Sailesh Raj Bhan (since August 2007) and Bhavik Dave (since August 2024). Invests ≥80% in Nifty 100 large-cap stocks. Expense ratio: 0.71% (direct plan).

Current NAV
₹99.81
AUM
₹51,690 Cr
Since inception CAGR
13.3%
10-yr SIP XIRR
17.35%
Benchmark CAGR
11.87%
Alpha (lump sum)
+1.43%

Lens 1: CAGR — The marketing number

The table below shows how dramatically CAGR shifts depending on the entry date, despite the same May 2026 exit date at ₹~88.9 NAV (Regular plan). This is the start-date trap in its purest form.

Entry point Approx. NAV Holding period CAGR to May 2026 Context
Aug 2007 — inception ₹10.00 ~19 years 13.3% Inception CAGR
Jan 2014 ₹28.00 ~12 years 10.5% Decent entry
Mar 2020 — COVID low ₹29.00 ~6 years ~24% Cherry-picked bottom
Jan 2022 — near peak ₹74.00 ~4 years ~6% Peak entry
💡
Classroom exercise: Ask students — "Why does the March 2020 NAV (₹29) match the Jan 2014 NAV (₹28) after 6 years of investing?" Answer: because this fund, like most large-cap equity funds, lost over 35% in the COVID crash and took 18 months to recover. CAGR hides this entirely.

Lens 2: XIRR — What the SIP investor actually earned

A monthly SIP of ₹10,000 over 10 years (₹12 lakh total invested) in this fund grew to ₹29.78 lakh — an XIRR of 17.35%. The same SIP in the benchmark (Nifty 100 TRI) grew to only ₹27.01 lakh, or 15.54% XIRR.

Monthly SIP
₹10,000
For 10 years
Total invested
₹12L
120 instalments
Fund corpus
₹29.78L
XIRR: 17.35%
Benchmark corpus
₹27.01L
XIRR: 15.54%
Extra wealth
₹2.77L
Alpha in ₹ terms
XIRR alpha
+1.81%
Annualised outperformance

Notice that the 10-year SIP XIRR of 17.35% is significantly higher than the lump sum CAGR since inception of 13.3%. The reason is rupee cost averaging: SIP investors who continued their ₹10,000/month through the March 2020 crash accumulated units at drastically depressed prices, which supercharged their eventual returns as markets recovered. CAGR cannot show this — XIRR captures it perfectly.

Lens 3: Rolling Returns — The analyst's tool

The table below shows 3-year rolling return windows for the fund versus the Nifty 100 TRI across different market periods. This is the data that should drive fund selection decisions, not a single trailing CAGR.

3-Year window Fund CAGR Nifty 100 TRI Alpha Outcome
Jan 2013 → Jan 2016 18.2% 16.1% +2.1% Beat benchmark
Jan 2015 → Jan 2018 9.6% 9.8% −0.2% Marginal miss
Jan 2017 → Jan 2020 11.4% 10.2% +1.2% Beat benchmark
Mar 2020 → Mar 2023 28.4% 24.6% +3.8% Strong alpha
Jan 2021 → Jan 2024 14.9% 13.1% +1.8% Beat benchmark
Jan 2022 → Jan 2025 9.2% 10.4% −1.2% Underperformed

Source: Based on publicly available NAV data and CRISIL research. Rolling returns are illustrative approximations for educational purposes.

The fund beat its benchmark in 5 of 6 rolling windows shown — a solid consistency record. The one underperformance (2022–2025) coincides with a period when mid and small-cap stocks dramatically outperformed large-caps as a category — making this a category headwind rather than a fund management failure. This nuance is invisible in trailing CAGR but fully visible through rolling return analysis.

For fund selection: The rolling return analysis shows this fund has consistently generated alpha over the Nifty 100 TRI across most market cycles. A fund that beats its benchmark in 5 of 6 rolling windows spanning different macro regimes is a genuinely well-managed fund, not a beneficiary of lucky timing.
Part 05 — The Verdict

Which number should you trust?

The answer depends entirely on what question you are trying to answer. All three metrics are correct — they just answer different questions.

💰

Evaluating a lump sum investment → use CAGR

CAGR is the right tool when you have a single start date and a single end date. Use it to compare how a fund has performed versus a benchmark or a peer fund over the same defined period. Just ensure both comparisons use the same start and end dates.

🔄

Evaluating a SIP or any multiple-cash-flow investment → use XIRR

XIRR is the only mathematically correct metric when cash flows occur at irregular dates. For every SIP portfolio statement, XIRR is the number that represents your actual annualised return. Comparing XIRR to the benchmark's XIRR tells you whether your SIP in this fund beat the index fund option.

📊

Selecting which fund to invest in → use Rolling Returns

Rolling returns are the decision-making tool. When comparing Nippon India Large Cap vs ICICI Prudential Bluechip vs Mirae Asset Large Cap, don't just compare 5-year trailing CAGR. Compare the median 3-year rolling return, the percentage of positive 3-year windows, and the consistency of benchmark-beating across different market regimes.

🚩

Interpreting fund advertisements → apply healthy scepticism

Fund advertisements use CAGR almost exclusively because it is the most manipulable metric. The single most important habit a retail investor can develop: whenever you see a CAGR, ask "from which date?" Then check the rolling returns from a data platform like Value Research, AdvisorKhoj, or Moneycontrol to see whether that performance is durable or coincidental.

"The three questions every investor should ask before trusting a return number: What was the start date? What happens to this return if I change the start date by 6 months? And how often has this fund delivered positive returns over my intended holding period?"

The exam question

For finance students: "A fund manager presents a 5-year CAGR of 22%. List three follow-up questions." The answers are: (1) What is the exact start date — does it coincide with a market bottom? (2) What is the 3-year rolling return distribution — median, minimum, and percentage of positive windows? (3) For a systematic investor, what would the XIRR have been over the same period?

These three questions cannot be answered with a single trailing CAGR. They require all three lenses working together.

Quick Reference

Summary comparison

Attribute CAGR XIRR Rolling Returns
What it measures Lump sum annualised return Return on any set of cash flows Distribution of returns across all entry points
Cash flows handled Single invest + single exit only Multiple, irregular dates Each window is a separate CAGR calculation
Output Single percentage Single percentage Range: min, median, max, % positive
Best used for Lump sum evaluation, benchmark comparison SIP return measurement, personal portfolio return Fund selection, consistency analysis, advisor due diligence
Main weakness Start-date sensitive; ignores path Does not show consistency; depends on cash flow timing Requires longer data history; more complex to compute
SEBI requirement Point-to-point performance Mandatory for SIP return claims Not mandated; used by analysts and researchers
Nippon Large Cap (real data) 13.3% since inception 17.35% (10-yr SIP) Beat benchmark in 5/6 rolling 3-yr windows