Rolling Returns vs Point-to-Point Returns: Why the Same Fund Shows Two Different Numbers

Two ways to measure the same fund

A point-to-point return picks two dates - say, 31 October 2023 and today - and reports the growth between them. It is simple, and it is the number most often quoted. The problem is that it depends entirely on the two dates chosen. Move the start date by a month and the number can change sharply, even though nothing about the fund itself changed.

A rolling return fixes this by testing every possible start date for a window of a given length, say one year, across the fund’s whole history, and reporting the whole distribution: a minimum, a maximum, a median, and everything in between. It answers a different question: not “what did this fund return from date A to date B,” but “what would an investor who bought on any given day over the fund’s history have actually earned, a year later.”

Thirty-five real one-year windows, one fund

Using 35 overlapping one-year windows for Parag Parikh Flexi Cap, computed monthly from 2021-10-31 through 2026-10-09, the one-year return ranged from -6.29% to 43.88%, with a median of 9.12%.

A single point-to-point figure - say, the most recent window’s -4.6% - tells you nothing about how unusual or typical that result was. Looked at against the full spread, it sits far from the best outcome an investor could have had (43.88%) and comfortably above the worst (-6.29%). That context is exactly what a point-to-point number, taken alone, cannot give you.

Why the spread matters more than any single number

The gap between the worst and best one-year window here is 50.17 percentage points, for the same fund, the same strategy, the same manager. None of those windows is wrong; each is a real, achievable outcome depending purely on when an investor happened to start. A wide spread means the fund’s short-term results are sensitive to timing. A narrow spread means they are not.

This is also why rolling returns are the standard way Punji computes category rankings and percentiles: ranking funds on one point-to-point window would really be ranking them on luck of timing as much as on skill.

How to read a rolling return table

Look at the median first, since it describes the typical outcome rather than the best or worst case. Then look at the worst window: could you have stayed invested through that outcome without panicking? A fund with a high median but a very ugly worst case needs a longer holding period than one whose worst case is mild. Compare the spread, not just the headline, between two funds in the same category before choosing.

Frequently asked questions

Why does Punji show rolling CAGR instead of a single return figure?

Because a single figure is one data point out of many possible ones, chosen by whoever picked the start and end dates. Rolling CAGR reports the distribution instead, which is harder to cherry-pick and closer to what a real investor experiences.

Is a 3-year point-to-point return ever useful?

It can be, as a quick snapshot, provided you also check how that window compares with the fund’s rolling distribution over the same length. Used alone, without that context, it is easy to make a fund look better or worse than its typical outcome by picking a flattering or unflattering start date.

How many windows does Punji use to compute rolling returns?

Every available window of the chosen length across the fund’s full NAV history, calculated monthly. A fund with five years of history and a one-year window has roughly 48 overlapping windows to draw the distribution from.