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HSBC NIFTY NEXT 50 INDEX FUND - Direct Growth is an index scheme managed by HSBC Mutual Fund. Over rolling three-year windows since inception, investors earned a median compounded return of 19.48%, with the bottom and top quartiles at 18.01% and 21.09% respectively. It has ranked in the top half of its category for 1 of the last 1 reported years. The total expense ratio is 0.33% on assets of ₹148Cr. The fund is currently managed by Rajeesh Nair, appointed within the last year.
Lower is better.
This scheme classifies as Large-Growth on the 3x3 equity style box, with 97% 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 |
|---|
| Hindustan Aeronautics Ltd | Industrials | 3.35% |
| TVS MOTOR COMPANY LIMITED | Consumer Cyclical | 3.34% |
| CUMMINS INDIA LIMITED | Industrials | 2.89% |
| Varun Beverages Ltd | Consumer Defensive | 2.86% |
| AVENUE SUPERMARTS LIMITED | Consumer Defensive | 2.75% |
| BRITANNIA INDUSTRIES LIMITED | Consumer Defensive | 2.74% |
| POWER FINANCE CORPORATION LTD. | Financial Services | 2.66% |
| BHARAT PETROLEUM CORPORATION LTD. | Energy | 2.48% |
| THE INDIAN HOTELS COMPANY LIMITED | Consumer Cyclical | 2.27% |
| CG POWER AND INDUSTRIAL SOLUTIONS LIMITED | Industrials | 2.27% |
| HDFC ASSET MANAGEMENT COMPANY LTD | Financial Services | 2.25% |
| SAMVARDHANA MOTHERSON INTERNATIONAL LIMITED | Consumer Cyclical | 2.18% |
| INDIAN OIL CORPORATION LIMITED | Energy | 2.16% |
| BANK OF BARODA | Financial Services | 1.99% |
| VEDANTA LIMITED | Basic Materials | 1.88% |
| Canara Bank | Financial Services | 1.85% |
| BAJAJ HOLDINGS AND INVESTMENT LTD. | Financial Services | 1.81% |
| REC LIMITED | Financial Services | 1.80% |
| GAIL (INDIA) LIMITED | Utilities | 1.79% |
| TORRENT PHARMACEUTICALS LIMITED | Healthcare | 1.78% |
| GODREJ CONSUMER PRODUCTS LIMITED | Consumer Defensive | 1.75% |
| PIDILITE INDUSTRIES LIMITED | Basic Materials | 1.74% |
| ADANI GREEN ENERGY LIMITED | Utilities | 1.67% |
| UNITED SPIRITS LIMITED | Consumer Defensive | 1.59% |
| ABB INDIA LIMITED | Industrials | 1.54% |
| Sector | Holdings | Weight |
|---|---|---|
| Financial Services | 11 | 20.84% |
| Capital Goods | — | 16.93% |
| Power | — | 11.82% |
| Fast Moving Consumer Goods | — | 8.94% |
| Automobile and Auto Components | — | 7.84% |
| Oil, Gas & Consumable Fuels | — | 6.43% |
| Metals & Mining | — | 6.27% |
| Healthcare | 2 | 6.05% |
| Consumer Services | — | 5.02% |
| Chemicals | — | 3.27% |
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.
| P75 |
|---|
| Max |
|---|
| Positive % |
|---|
| 1Y | -13.42% | -0.18% | 12.37% | 56.83% | 72.83% | 73.9% |
| 3Y | 15.35% | 18.01% | 19.48% | 21.09% | 24.09% | 100.0% |
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 27.6% 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.