Rolling & Point-to-Point Returns Analysis of Large Cap Mutual Funds

Introduction

The debate between active and passive investing has become increasingly relevant in the Indian mutual fund space. Active funds aim to beat the market through skilled stock picking and tactical allocation, while passive funds simply replicate benchmark indices at lower costs. Evaluating which strategy has worked better requires looking beyond single-period snapshots, as market cycles, economic conditions, and fund management styles can distort short-term outcomes.

To overcome this, both point-to-point (PTP) returns and rolling returns are used in this analysis. While PTP returns capture performance between two fixed dates, they often suffer from timing bias. Rolling returns, on the other hand, provide a more reliable measure of consistency by averaging outcomes across overlapping periods.

Point-to-point returns measure the performance of an investment between two fixed dates—for example, the 5-year return of a fund from January 2018 to January 2023. While simple to calculate and widely used, point-to-point returns have a major flaw: they suffer from starting point bias (when the start date is fixed) or ending point bias (when the end date is fixed).

This bias means the performance can look artificially good or bad depending on the market conditions around those chosen dates.

Rolling returns solve this problem by calculating returns over overlapping periods instead of fixing a single start or end point. For instance, if we want to measure 3-year rolling returns from 2005 to 2020, we calculate returns for 2005–2008, 2006–2009, 2007–2010, 2008–2011, and so on, until the most recent 3-year period.

By averaging these results, rolling returns give a more consistent and unbiased picture of a fund’s performance. This helps investors understand whether a fund’s outperformance is sustainable across market cycles or just a result of favorable timing.

Methodology

To evaluate how active and passive funds stack up against each other, we followed this structured approach:

1. Fund Selection

   Large-Cap Mutual Funds:

   29 actively managed large-Cap funds

   24 passive large-Cap funds

   
   

2. Return Measurement

   Point-to-Point Returns: Calculated for 1-year, 3-year, 5-year, and 10-year periods.

   Rolling Returns: We have sourced 3-year rolling periods from Rolling Returns Of Mutual Funds vs Mutual Fund Benchmark | Advisorkhoj, India to assess consistency over time.

   
   

3. Benchmarking

   Each fund was compared with its respective benchmark index (e.g., Nifty 100 TRI for large-Cap, Nifty 50).

   
   

4. Performance Evaluation

   We checked how many large funds outperformed their benchmark across different time frames.

   We also calculated the average return of large-Cap funds to measure whether active management provided any meaningful advantage after fees.

Outperformance of Large-Cap mutual funds (Point-to-Point Returns till June 2025)

Large-Cap Active Funds (29 funds)

• 1-Year (Jun 2024 – Jun 2025): 15 funds (51.72%) outperformed

• 3-Year (Jun 2022 – Jun 2025): 19 funds (65.52%) outperformed → best performance period

• 5-Year (Jun 2020 – Jun 2025): 12 funds (41.38%) outperformed → weakest phase

• 10-Year (Jun 2015 – Jun 2025): 17 funds (58.62%) outperformed

Large-Cap Index (Passive) Funds (24 funds)

• 1-Year: 0 outperformed

• 3-Year: 0 outperformed

• 5-Year: 0 outperformed

• 10-Year: 0 outperformed

None of the Index funds outperformed, which is predictable because their aim is to follow the market and not to beat it. Passive index funds generally have lower expense ratios compared to active funds, though investors should still account for tracking error and other incidental costs.

Performance of Large-Cap Mutual Funds vs. Benchmark

(Point-to-Point Returns till June 2025)

1. Short-term (1Y): Active funds underperform benchmarks (Nifty 100) and also the large-Cap index fund, showing the difficulty of beating the index (Nifty 50) in volatile markets.

2. Medium-term (3–5Y): Active funds deliver higher returns, proving fund managers’ alpha (excess returns) generation ability.

3. Long-term (10Y): Returns of active and benchmarks converge, highlighting market efficiency and fading alpha.

4. Passive funds: Stay close to benchmarks but slightly lag due to costs and tracking error.

Performance Analysis of Large-Cap funds vs the Benchmark using rolling returns

Key Observations:

1. Active Funds Lead:

   Large-Cap Active Avg Returns = 14.44%

   This is higher than Nifty 100 (13.93%), Nifty 50 (13.55%), and Large-Cap Passive (13.70%).

   Shows that active funds, on average, created alpha over benchmarks in rolling 3-year periods.

   
   

2. Outperformance Data:

   19 times (65.52%) Active funds outperformed benchmarks.

   Only 13 times (0.54%), Passive funds outperformed benchmarks by only 0.5% - 1.5%.

   
   

3. Funds like Aditya Birla Sun Life, Axis, ICICI Prudential, Mirae Asset, and SBI Active Large-Cap delivered small excess returns of around 0.5–2.5% but have given consistent returns from their inception.

   
   

4. A few funds (e.g., Franklin India, LIC MF, Taurus) underperformed consistently, especially in post-COVID periods or due to higher costs.

   
   

5. Certain large-Cap index funds such as Axis Nifty, DSP Nifty, LIC MF, Taurus, and Tata BSE Sensex Index Fund have been very consistent in mirroring their benchmarks across both bullish (good) and bearish (bad) market phases.

Conclusion

Point-to-point (PTP) returns can often create a misleading picture as they depend heavily on the start and end dates chosen. For instance, in the earlier graph, the 3-year PTP returns appeared in the 18–20% range, but rolling return analysis shows the actual performance lies between 13–15%. This demonstrates that rolling returns are a better measure of consistency and true fund performance.

FAQs

How to find mutual fund rolling returns?

Mutual fund rolling returns are found by calculating performance over overlapping periods. For example, in 3-year rolling returns from 2010 to 2020, you measure 2010–2013, 2011–2014, 2012–2015, and so on, then average the outcomes. This removes the bias of choosing a single start or end date.

What is the difference between CAGR and rolling returns?

CAGR (Compound Annual Growth Rate) measures growth between two fixed dates, assuming the investment compounded steadily. Rolling returns, by contrast, calculate returns for multiple overlapping periods, which better reflects consistency. CAGR answers “how much did my investment grow,” while rolling returns answer “how consistently has it performed.”

What is a 3-year rolling return?

A 3-year rolling return shows the average annual return of a mutual fund over every consecutive 3-year period. It helps investors check whether performance is steady across different time frames, instead of relying on just one fixed start and end date.

Are rolling returns better than average returns?

Yes, rolling returns are generally better for evaluating mutual funds. Average returns can be distorted by extreme highs or lows in one period, giving a misleading picture. Rolling returns, by spreading results across many periods, reveal whether a fund consistently outperforms its benchmark across market cycles. This makes them more reliable for long-term evaluation.