Does fund size hurt returns? What the cross-section shows
The largest quintile returned 3.99% against 6-7% elsewhere. Here's why that proves almost nothing.
"Does a fund get worse as it gets bigger?" is one of the genuinely open questions in Indian mutual funds. We can't answer it properly from one date's data — but we can show what the cross-section looks like, and the shape is worth seeing.
Equity funds by size quintile
| Quintile | AUM range (₹ Cr) | Funds | Median 1Y return | Median TER |
|---|---|---|---|---|
| Q1 (smallest) | 6 – 462 | 114 | 6.09% | 0.76% |
| Q2 | 462 – 1,279 | 114 | 7.16% | 0.72% |
| Q3 | 1,281 – 2,756 | 114 | 6.04% | 0.68% |
| Q4 | 2,771 – 7,354 | 114 | 6.47% | 0.65% |
| Q5 (largest) | 7,373 – 133,448 | 118 | 3.99% | 0.64% |
Two things move. Expense ratios fall steadily with size — 0.76% in the smallest quintile down to 0.64% in the largest, which is what the regulatory slab structure is designed to produce. And the largest quintile shows a materially lower median one-year return: 3.99% against roughly 6–7% for everyone else.
Why you should not read that as "big funds underperform"
Three reasons, and they matter more than the finding.
One window, one date. This is a single one-year period ending on one day. A different year could easily invert it. Nothing here establishes a persistent relationship.
Size correlates with strategy. The largest equity funds are overwhelmingly large-cap and flexi-cap; the smallest skew toward sectoral, thematic and newer niche mandates. So the quintiles differ by category as much as by size, and over this particular year the categories performed differently. The size effect and the category effect are entangled and this table cannot separate them.
No significance test. We have not computed whether the gap between quintiles is larger than the noise, and by our own standard we don't get to call something a finding until we have. This is a description of a cross-section, not a claim.
What would actually answer the question
You'd need to track individual funds as their AUM grew, within category, across multiple market cycles — asking whether a given fund's returns deteriorated as it scaled, not whether big funds differ from small ones today. That needs historical snapshots we haven't assembled.
The theoretical case, for what it's worth
The argument that size hurts is straightforward: a large fund cannot take a meaningful position in a small company without moving the price, so its opportunity set narrows as it grows. A ten-thousand-crore fund buying a two-thousand-crore company either takes a token position that can't affect returns, or a large one it can't exit quickly.
That constraint is real and it binds hardest on small- and mid-cap mandates. It's much weaker for large-cap funds, where the investable universe is deep enough to absorb size.
The counter-argument is that scale lowers costs, and the expense column above shows that happening — roughly 0.12 percentage points between the extreme quintiles. That's a real, permanent, compounding advantage, unlike a single year's return gap.
What we'd suggest taking from it
Not "avoid large funds". Rather: fund size is a structural fact worth knowing alongside the mandate, because the size constraint bites very differently on a small-cap fund than on an index fund, and a one-year return column can't tell you which effect you're looking at.
Key takeaways
- Median TER falls from 0.76% in the smallest AUM quintile to 0.64% in the largest.
- The largest quintile showed a median 1Y return of 3.99% vs roughly 6-7% for the rest.
- Size correlates strongly with mandate, so the size and category effects are entangled.
- One window, one date, no significance test — this is a description, not a finding.
- Answering the question properly needs per-fund histories tracked as AUM grew.
See these ideas on real stocks
StockLearn runs this read on ~2,000 NSE stocks every evening. Nifty 50 is free, no login.
Browse today's scan →This guide reports measured statistics from public AMFI NAV data for a single date. It is educational and is not investment advice or a recommendation of any fund. Past performance does not indicate future results.