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UTI Nifty Midcap 150 Index Fund - Direct Plan - Growth Option is an index scheme managed by UTI Mutual Fund. It has ranked in the top half of its category for 1 of the last 1 reported years. The total expense ratio is 0.62% on assets of ₹66Cr. The fund is currently managed by Mr. Ayush Jain, appointed within the last year.
Lower is better.
This scheme classifies as Large-Blend on the 3x3 equity style box, with 86% of its portfolio classified as of 2026-05-29.
| Holding | Sector |
|---|
| Window | Min | P25 | Median |
|---|
Point-in-time CAGRs cherry-pick a single start date. The chart below shows the distribution of every possible rolling start over the fund's history, so you see the range of investor outcomes — not just one date's number.
Backtested SIP outcomes across both rolling-window scenarios and named historical stress events (COVID, Election uncertainty, Russia/Ukraine, etc.), plus per-manager alpha during their tenure on this scheme.
Same fund, monthly SIPs over rolling 1/3/5-year windows.
Mutual fund investments are subject to market risks. Read all scheme-related documents carefully. Past performance is not indicative of future results. MintByte is an AMFI-registered Mutual Fund Distributor (ARN-314872) and APMI member (APRN-01658). MintByte does not issue buy/sell recommendations on specific securities — the site is an educational data and analytics platform. Star ratings on this page reflect a 3-year category-quartile position computed in-house and are educational only.
Mutual fund schemes are subject to market risk. Read all scheme-related documents carefully before investing. Past performance is not indicative of future results. MintByte is an AMFI-registered mutual fund distributor (ARN-314872). MintByte does not issue buy/sell recommendations on specific securities — the site is an educational data and analytics platform. Not investment advice. Methodology · How we earn.
ETF-specific data. Tracking error is the standard-deviation of (ETF return − index return) over the trailing year.
In-house derivations using 3-year daily NAV vs benchmark. See methodology.
| Weight |
|---|
| BSE LIMITED | Financial Services | 3.79% |
| THE FEDERAL BANK LIMITED | Financial Services | 1.80% |
| SUZLON ENERGY LIMITED | Industrials | 1.72% |
| HERO MOTOCORP LIMITED | Consumer Cyclical | 1.69% |
| INDUSIND BANK LIMITED | Financial Services | 1.54% |
| AU SMALL FINANCE BANK LIMITED | Financial Services | 1.46% |
| PB FINTECH LIMITED | Financial Services | 1.45% |
| LUPIN LIMITED | Healthcare | 1.42% |
| INDUS TOWERS LIMITED | Communication Services | 1.35% |
| Persistent Systems Ltd | Technology | 1.33% |
| BHARAT HEAVY ELECTRICALS LIMITED | Industrials | 1.31% |
| BHARAT FORGE LIMITED | Consumer Cyclical | 1.28% |
| FORTIS HEALTHCARE LIMITED. | Healthcare | 1.23% |
| ASHOK LEYLAND LIMITED | Industrials | 1.18% |
| IDFC FIRST BANK LIMITED | Financial Services | 1.18% |
| DIXON TECHNOLOGIES (INDIA) LIMITED | Technology | 1.17% |
| LAURUS LABS LIMITED | Healthcare | 1.09% |
| POLYCAB INDIA LIMITED | Industrials | 1.09% |
| HITACHI ENERGY INDIA LIMITED | Industrials | 1.08% |
| MAX FINANCIAL SERVICES LIMITED | Financial Services | 1.07% |
| MARICO LIMITED | Consumer Defensive | 1.04% |
| AUROBINDO PHARMA LIMITED | Healthcare | 0.99% |
| Swiggy Pvt Ltd | Consumer Cyclical | 0.94% |
| SRF LIMITED | Industrials | 0.93% |
| GLENMARK PHARMACEUTICALS LIMITED | Healthcare | 0.92% |
| Sector | Holdings | Weight |
|---|---|---|
| Financial Services | 28 | 27.94% |
| Capital Goods | — | 14.01% |
| Healthcare | 15 | 9.55% |
| Automobile and Auto Components | — | 6.78% |
| Consumer Services | — | 5.20% |
| Information Technology | — | 4.81% |
| Consumer Durables | — | 4.49% |
| Fast Moving Consumer Goods | — | 4.27% |
| Chemicals | — | 3.86% |
| Metals & Mining | — | 3.59% |
Active bets vs the average Index fund. Biggest deviations shown first.
Accent bar = fund's actual sector weight. Vertical black tick = category average for the same sector. Green overlay = overweight, dashed red = underweight. The biggest active bets show first.
How crowded into the same stocks is this fund vs the largest fund in its category?
Category leader = highest-AUM scheme in the same SEBI category. A high overlap-of-weight number means the fund is concentrated into the same names as the leader (crowded); a low one means it's genuinely differentiated.
| P75 |
|---|
| Max |
|---|
| Positive % |
|---|
| 1Y | -0.44% | 5.41% | 8.55% | 12.94% | 23.16% | 99.2% |
Each cell is one year. Q1 = top quartile within the AMFI category for that period. Cell label is the last two digits of the year.
Top-10 weight 17.5% means the portfolio is broad — even the top names don't dominate. Effective-N is the inverse Herfindahl index — a measure of "how many positions effectively drive the fund" after weighting. Category: Index.
Compounding maths on a notional ₹10 lakh lumpsum at 12% gross annual return. Green bar is what you'd have without the fee; red overlay is the fee drag. Fee is constant in this scenario — actual outcomes depend on real returns and any future TER changes.
What an investor SIPping into this fund actually got during named market shocks.
Each row is a back-tested SIP — monthly contribution over the regime's duration, no fees adjustment beyond NAV-baked TER. XIRR is the annualised IRR of those cashflows; Abs return is the absolute cash-on-cash; Max DD is the deepest drawdown experienced mid-investment. Past performance is not indicative of future results.
Alpha is the annualised excess return vs benchmark over the manager's tenure on this scheme. Beat-benchmark = total return beat the index over the same window.
Does the fund get worse as it gets bigger? Each dot is one historical manager-tenure: AUM at tenure-end vs alpha delivered during that tenure.
Correlation is too weak to confirm or rule out capacity-driven alpha decay. Re-evaluate as more manager-tenure data accumulates.
Each dot is one manager-tenure: X = AUM at tenure end, Y = alpha during that tenure. Connecting line in chronological order. Pearson r measures the linear relationship between AUM and alpha across the historical record. n = 2 data points.