Rolling returns vs trailing returns in mutual funds

Rolling returns and trailing returns are two methods of computing mutual fund performance over a given time horizon (say, 3 years or 5 years). Both express the fund’s return as a compounded annual growth rate (CAGR) over the measurement period. The fundamental difference is: a trailing return is a single snapshot measured from a specific past date to today, while rolling returns compute that same CAGR for every possible starting date in the historical record, producing a distribution of returns rather than a single number.

Rolling returns are the academically preferred method for evaluating mutual fund track records because they are not biased by the choice of start date.

Trailing returns: definition and formula

A trailing return (also called “point-to-point return”) is the CAGR from a specific point in the past to the current date:

\[ \text{Trailing CAGR} = \left(\frac{\text{NAV}\text{today}}{\text{NAV}{n \text{ years ago}}}\right)^{1/n} - 1 \]

For example, a fund’s “3-year trailing return” as of 12 May 2026 is the CAGR from 12 May 2023 to 12 May 2026.

Trailing returns are the standard disclosure in AMC factsheets, AMFI data, and comparison portals (Value Research, Morningstar India). They are widely published because they are simple to compute and communicate.

Limitation: period sensitivity (start-date bias)

The critical weakness of trailing returns is that the result is entirely determined by the choice of measurement period endpoints. A fund’s trailing 3-year return will be very different depending on whether:

• The measurement period starts in a market trough (inflating the return)
• The measurement period starts at a market peak (depressing the return)
• The measurement period ends during a market rally vs a crash

For instance, a fund’s trailing 3-year return measured from:

• March 2020 to March 2023 (starts at COVID crash, ends mid-recovery): likely very high
• January 2018 to January 2021 (starts pre-crash): moderate

The fund’s actual management quality has not changed, only the measurement window has.

Rolling returns: definition and formula

A rolling return computes the CAGR for every possible start date within a historical data window, using a fixed rolling period (e.g., 3 years):

For each date \(t\) from the beginning of the data window to \(T - n\):

\[ \text{Rolling CAGR}t = \left(\frac{\text{NAV}{t+n}}{\text{NAV}_t}\right)^{1/n} - 1 \]

If the data goes back 10 years (daily NAV), there are approximately 7 years × 252 = 1,764 distinct 3-year rolling return observations. These are plotted or summarised statistically.

Summary statistics from rolling returns:

• Median rolling 3-year CAGR: The typical 3-year outcome the fund has delivered.
• Minimum rolling 3-year CAGR: Worst case among all 3-year periods, equivalent to maximum drawdown in a return-based framework.
• Percentage of positive 3-year rolling periods: What fraction of investors who held for 3 years made money.
• Standard deviation of rolling returns: Consistency of the fund’s performance.

Illustrative comparison

Consider Fund A and Fund B with identical trailing 5-year returns of 14% (as of May 2026):

Fund A rolling 5-year CAGR statistics:

• Median: 13.8%
• Minimum: 6.5%
• Maximum: 22.0%
• % positive periods: 95%

Fund B rolling 5-year CAGR statistics:

• Median: 11.2%
• Minimum: −2.0%
• Maximum: 28.0%
• % positive periods: 78%

Fund B has a negative minimum rolling return and lower median, indicating it has been more volatile and has actually underperformed Fund A over most holding periods, despite an identical trailing 5-year return. The trailing number coincidentally matches because Fund B happened to have a strong recent 3-year run.

Rolling returns and the comparison of active vs passive funds

Rolling returns are the standard tool for evaluating whether an active fund consistently beats its benchmark:

In this example, the active fund beats the benchmark in 62% of 3-year rolling periods. This is more informative than a single trailing return comparison.

For large-cap equity funds in India, rolling return analysis typically shows that:

• Over 3-year rolling periods (2010–2024), ~55–65% of large-cap funds beat the Nifty 100 TRI.
• Over 5-year rolling periods, the active-over-passive success rate falls to ~40–55%, suggesting decreasing alpha generation over longer periods.
• In the direct plan era (post-2013), the success rate has declined further because direct plan TER is lower.

CAGR and rolling returns relationship

All rolling returns are expressed as CAGRs. The distinction between CAGR and rolling returns is not a mathematical difference, CAGR is the formula used, and rolling is the methodology (applying that formula repeatedly across multiple windows). See CAGR vs XIRR for the distinction between CAGR and XIRR.

Rolling vs trailing in TER impact analysis

Rolling return analysis powerfully demonstrates the long-term TER drag. For two plans of the same fund (direct: 1.00% TER, regular: 1.90% TER):

• Over a 10-year rolling window, the direct plan outperforms the regular plan in 100% of periods.
• The median excess return of the direct plan over the regular plan over all rolling 10-year windows ≈ 0.90 percentage points per annum, compounding to a substantial corpus difference.

Where to find rolling return data in India

AMFI factsheets show only trailing returns. Rolling return data is available through:

• Value Research (valueresearchonline.com): Rolling return charts for all funds.
• PrimeInvestor (primeinvestor.in): Detailed rolling return statistics including minimum, median, maximum, and % positive periods.
• Morningstar India (morningstar.in): Rolling return visualisation tools.
• Freefincal (freefincal.com): Rolling return analysis tools and articles.

SEBI has not mandated rolling return disclosure in factsheets but encourages platforms and advisers to use rolling return analysis.

See also

• CAGR vs XIRR in mutual funds
• XIRR for SIP returns
• Alpha (Jensen’s alpha) in mutual funds
• Maximum drawdown
• Total expense ratio in mutual funds
• Mutual fund

References

1. AMFI, Trailing return disclosure methodology, amfiindia.com.
2. Value Research, Rolling return data and methodology, valueresearchonline.com.
3. PrimeInvestor, Rolling return statistics for Indian mutual funds, primeinvestor.in.
4. SEBI, Standardised performance disclosure circular, 2012.
5. Freefincal, Rolling return analysis framework, freefincal.com.