Deep hole on the path
Max drawdown reached -29.5%. That is a hard stretch for anyone checking the account monthly. The deepest trough lasted about 25 months.
Month-end returns from daily AMFI NAV, with return next to max drawdown. Watch, compare up to four of the same type, or read the tearsheet. Not SEBI PMS TWRR.
Nippon India Mutual Fund · AMFI code 140094
Age: 119 months · as of 2026-10-07 · AMFI NAV · data via MFAPI · AUM Not reported
Trailing return from month-end NAV
Research sheet
Growth of ₹100, underwater drawdown, rolling 12-month returns, and worst episodes from month-end AMFI NAV. AUM stays Not reported. Exchange traded price and premium/discount stay Not reported.
Rolling CAGR (3Y)
11.10%
Rolling CAGR (5Y)
11.68%
Survivorship note
Rolling CAGR uses consecutive month-end AMFI NAV returns. A closed scheme stays on its last filed NAV date.
Reported metrics only · not advice
Max drawdown reached -29.5%. That is a hard stretch for anyone checking the account monthly. The deepest trough lasted about 25 months.
Best year hit +37.7%. Worst calendar year was -10.0%. A +48% gap means the year you enter can dominate how the track feels.
Worst rolling year hit -19.2%. The best rolling year was +67.5%, so trailing windows swing hard both ways. One bad trailing window is a poor reason to judge the whole path.
Roughly 75% of the track sat under a previous peak. New highs were the exception, not the week-to-week norm.
121.35%
8.34%
52.94%
-29.49%
15.69%
0.53
0.60
52.9%
How has Nippon India ETF Nifty 50 Shariah BeES - Direct Plan performed?
CAGR 8.34% and max drawdown -29.49% (Nippon India Mutual Fund) from month-end AMFI NAV as of 2026-10-07. These are not SEBI PMS TWRR.
Why might a window say Not reported?
Trailing 1Y, 3Y, and 5Y need that many consecutive month-end NAV returns. A short or gappy track stays Not reported instead of an annualized guess.
Can I compare this with a PMS on one screen?
Open the PMS strategy and this scheme side by side. The compare tray here is ETF only, because daily NAV and SEBI monthly TWRR are different methods.