Rolling returns measure a fund's performance over every possible holding period of a given length — the most statistically honest way to evaluate consistency of returns.
Point-to-point returns only show performance between two specific dates — which can be cherry-picked. Rolling returns calculate the average annual return for every overlapping holding period of a fixed length (e.g., every 1-year period from January 2014 to January 2025, then Feb 2014 to Feb 2025, and so on). This generates hundreds of data points that show how often the fund delivered positive returns, what its average was, and how consistent it was across different starting dates.
Imagine a fund delivered 18% last year. Impressive! But what if you'd invested a year earlier and gotten -3%? Or two years earlier and gotten 25%? Rolling returns show all these 'starting point scenarios' at once — giving you the full picture of what investors actually experienced, not just what the fund did in the best or most recent period.
Choose a rolling window: 1 year, 3 year, 5 year.
Calculate the annualised return for every overlapping window across the fund's history.
E.g., for 3-year rolling returns: calculate return from Jan 2010–Jan 2013, then Feb 2010–Feb 2013, etc.
Plot or analyse the distribution: average rolling return, % of times the return was positive, minimum and maximum.
Compare across funds or against benchmark using the same rolling window.
Fund A: 5-year point-to-point return from Dec 2019 to Dec 2024 = 18% CAGR (looks excellent). Fund A: 3-year rolling returns across all periods (2010–2024): - Average: 11.2% - Minimum: -3.5% (investors who started in Jan 2018 and held until Jan 2021) - % of periods with negative 3-year returns: 12% The rolling analysis reveals that ~12% of investors who held for 3 years still lost money — important context behind the headline number.