As the Jul 2026 factsheet printed it: standard deviation 17.6% · portfolio turnover 0.24×. Exit load and minimum investment are not yet extracted from the scheme documents.
What only Anveshan can tell you
measured from the disclosures, not quoted from a brochure — each links to how it was done
P5Cost, measured
Cannot be measured: needs both a Direct and a Regular growth class.
The Regular and Direct plans hold the same portfolio; the Regular one pays a distributor out of your money every day. The gap between the two NAVs is that cost, measured from the NAVs rather than quoted from a document.
A return earned before they arrived is the house's record, not theirs — the tenure table shows the fund against its category over exactly their months.
Not replicated: the portfolio cannot be priced line by line in this build.
Each day, the NAV the fund published against the NAV its last disclosed portfolio would have produced at that day's prices. A gap that opens and stays is a change the fund has made and not disclosed yet.
Beat its category in 70% of three-year stretches, and averaged +1.7 points a year across all of them
83 rolling windows since 2016 · ahead by 5.0 points a year when it won, behind by 6.0 when it lost. A single five-year figure depends on the day you look; the share of stretches won does not — and the average margin says whether winning often was worth anything.
headline and record disagree 2 checks found the headline number and the underlying record pointing different ways — marked on the cards below.
NAV and drawdown
Regular plan class · as of 21 Sep 2026
Month-end NAV, indexed to 100 at Nov 2016
119 month-ends · ₹283.38 → ₹937.46, 3.3× since Nov 2016
Deepest fall (max drawdown)
−20.9%
27 Sep 2024 → 28 Feb 2025
Worst month
−10.2%
Mar 2026
Days to recover
308
from the deepest trough back to the old high
Drawdown is measured on the last year of daily NAV; trailing returns are CAGR of the regular growth class. A single end date decides them — the consistency card (P4) below is the record that does not, and it reports both how often the fund beat its category and by how much, because the first without the second can point the wrong way.
Holdings
Aug 2026 disclosure · 33 lines · when each was first held and the change over the last three disclosures
Showing 26–33 of 33 · page 2 of 2rows per page102550all
Largest sectors, Aug 2026 · grey: a year ago
Petroleum Products24.1% · 23.5%
Telecom - Services16.0% · 16.6%
Construction12.6% · 12.6%
Power10.0% · 11.0%
Cement & Cement Products8.5% · 9.9%
Healthcare Services5.8% · 4.8%
Auto Components3.5% · 2.1%
Electrical Equipment3.2% · 2.1%
share of the book05%10%15%20%25%
By market cap, Aug 2026
Large cap86.3%
Mid cap13.5%
Cash & equivalents0.2%
share of the book025%50%75%100%
Composition by market cap, month by month — what the fund actually held against what its label says
Large cap 86%
Mid cap 14%
Small / micro 0%
Cash & other 0%
The seven checks, in full
each: the plain claim, where it sits in the category, and — folded — how it is measured and the case against. A flag fires only where headline and record disagree.
P4Consistency, not a single end dateheadline and record disagree
Beat its category in 70% of three-year stretches, and averaged +1.7 points a year across all of them
83 rolling windows since 2016 · ahead by 5.0 points a year when it won, behind by 6.0 when it lost
What this means. Take every three-year stretch since the fund had a NAV, one starting each month, and ask two things of each: did it beat the typical fund in its category, and by how much. Counting the wins tells you the record does not depend on when you happen to look; averaging the margin tells you whether winning often was worth anything, because four small wins do not pay for one large loss.
How often, and by how much. The count and the average agree. Ahead by 5.0 points a year in the 58 windows it won and behind by 6.0 in the 25 it lost, so the average across all 83 is +1.7 points. The worst window ended Dec 2020, 10.1 points behind.
70%
lowest in categoryhighest in category
75th percentile · top quartile of 122 funds · category median 30%
windows measured83windows won58average across every window+1.70 pts a year · median +2.21when ahead, by how much+5.00 pts a year over 58 windowswhen behind, by how much−5.95 pts a year over 25 windowsworst window−10.10 pts a year, ended Dec 2020best window+10.36 pts a year, ended Jun 2024non-overlapping windows in that span3 — the rolling count overlaps, this does not
Fund minus category, each rolling three-year window
ahead of categorybehind
Each bar is one window's margin in percentage points a year. The height of the bars, not the count of green ones, is what the average across every window measures.
A modest five-year number over a record that beat its category 70% of the time. Rolling every three-year window forward month by month gives hundreds of overlapping observations instead of one. This fund was ahead of its category median in 70% of them, which points the opposite way to the headline figure. A single end date decided that headline.
How it is measured, and the case against
A fund that beats its category in most rolling three-year windows has a record; one that beats it in a few has an end date. How often it won and by how much are different questions, and this card answers both, because a fund can win four windows in five and still be behind across all five.
How often has it beaten its category, across every window?
Why this might matterRolling every three-year window forward month by month gives hundreds of overlapping observations instead of one. A single end date decides a headline five-year figure; the share of windows won cannot be flattered by when you happen to look. The average margin across every window is that share and the payoff multiplied together — win share x average beat plus loss share x average shortfall is exactly the average — so a high share bought with a few ruinous windows cannot hide behind the count.
Why it might notRolling windows overlap heavily, so they are not independent observations and the true sample is far smaller than the count suggests.
P5Cost, measured
Not measurable yet. Needs a Direct and a Regular growth class with overlapping NAV history.
What this means. The Regular and Direct plans hold the same portfolio; the Regular one pays a distributor out of your money every day. The gap between the two NAVs is that cost, measured from the NAVs rather than quoted from a document.
How it is measured, and the case against
The Direct plan is the same portfolio, priced differently; the divergence of the two NAVs is the cost, measured rather than quoted.
What does the Regular plan actually cost against its Direct twin?
Why this might matterSame manager, same holdings, same day. The gap between the two NAV series is the one number on this page that is knowable today rather than hoped for, and it compounds for as long as the units are held.
Why it might notA Regular plan buys advice. If that advice stops someone selling in a drawdown it can be worth more than the fee — the cost is visible and the behavioural saving is not, which makes this comparison unfair in exactly one direction.
P1Churn, and what it bought
Turns over 33% of the portfolio a year
−0.08 pts of excess return per unit of turnover
What this means. How much of the portfolio was bought and sold in a year, computed from what the fund disclosed each month. Trading costs something certain; the extra return it is meant to buy is not.
33% a year
costliest in categorycheapest in category
73th percentile · above median of 158 funds · category median 43%
excess return per unit of turnover−0.08 pts
How it is measured, and the case against
Turnover measured from consecutive disclosures — Σ|Δweight|/2 — costs something certain; the excess return it is meant to buy is not.
Is the trading paying for itself?
Why this might matterAMCs define their own turnover figure inconsistently. This one is computed from what the fund disclosed month to month, so two funds are comparable on it. Read it beside the excess return per unit of turnover.
Why it might notTurnover computed from month-end snapshots misses everything bought and sold inside a month, and a fund forced to sell by redemptions is charged for churn it did not choose.
P2Conviction or inertia
Typical top-10 holding kept 113 months
What this means. How long a typical top-10 position has been in the top ten. Long-held positions are a decision; a top ten that changes every quarter is a reaction.
113 months
lowest in categoryhighest in category
95th percentile · top decile of 160 funds · category median 27 months
active sharenot yet computable — needs index constituent files
How it is measured, and the case against
The median months a top-10 position has been held separates a portfolio somebody chose from one that drifted.
How long does a top-10 position stay a top-10 position?
Why this might matterConcentration is how a manager expresses conviction, and persistence is how long they keep it. Long-held positions with a rising weight are a decision; a top ten that turns over every quarter is a reaction.
Why it might notPersistence without active share is inertia: a portfolio of 166 names that tracks its category closely has diversified away the reason to pay for it. Active share needs index constituent files, which are not loaded yet.
P3Hit rate of the top ten
6 of 10 top picks beat their peers over the next 6 months, and averaged 1.9 points ahead of them
1120 positions judged, one disclosure at a time · ahead by 13.1 points when it won, behind by 12.1 when it lost
What this means. Take each month's ten largest holdings and check whether each one beat the typical stock its category holds over the next six months, and by how much. A blended return can hide two wins and eight losses; a count of wins can hide one position that lost half its value.
How often, and by how much. The count and the average agree. Ahead by 13.1 points in the 624 positions it won and behind by 12.1 in the 496 it lost, so the average across all 1120 is +1.9 points. The worst position was INE397D01024 at the May 2020 disclosure, 55.8 points behind.
56%
lowest in categoryhighest in category
64th percentile · above median of 145 funds
positions judged1120beat the median stock624average across every position+1.92 pts · median +1.95when ahead, by how much+13.08 pts over 624 positionswhen behind, by how much−12.13 pts over 496 positionsworst position−55.76 pts, INE397D01024 at the May 2020 disclosurebest position+75.12 pts, INE397D01024 at the Oct 2019 disclosure
How it is measured, and the case against
A manager's largest bets, judged one by one over the following six months, say more than the fund's blended return — and how far each one beat or missed the median stock says more than counting how many did.
Of its top-10 positions, how often did they beat the category-median stock?
Why this might matterA fund can beat its category on two positions and lose on eight; the hit rate shows the pattern the aggregate hides. The average margin then shows what the hit rate hides in turn: six winners worth a point each do not pay for four losers worth ten, and only the margin says which happened.
Why it might notSix months is short, sizing matters more than counting, and a manager who is right on the biggest position and wrong on nine small ones has done their job — the margins here are unweighted, so they answer the counting question better, not the sizing one. Overlapping disclosures judge the same position again each month it is held, so one long-held winner is counted many times. And this is a description of six months already past, not a forecast of the next six.
P6Size against edge
₹186 Cr, 55th percentile in category; 85% of growth came from inflows
smaller than 45% of the funds in its category (160 funds) · AUM Sep 2023 → Jul 2026 · Regular plan expense ratio 0.00%
What this means. Where the fund sits by size in its category, and how much of its growth was money arriving rather than the portfolio compounding. A very large fund cannot buy what a small one can; size should buy a lower fee in return.
55th percentile by AUM
largestsmallest
45th percentile · below median of 160 funds
median holding weight, trendflatexpense ratio, Regular / Direct0.00% / 0.52% · category median 0.16%AUM, Sep 2023 → Jul 2026₹43 Cr → ₹186 Cr (+68% a year)of that change, from flows rather than returns85% net inflows · NAV +50% over the window
Assets under management, ₹ crore, Dec 2016 – Jul 2026
52 points · months without a factsheet figure use AMFI's quarterly average · Regular-plan expense ratio 0.00% in Jun 2018 → 0.00% in Sep 2026
How it is measured, and the case against
Past a certain size the smaller end of a mandate becomes unreachable, and the fund starts to look like its index; what size should buy in return is a lower expense ratio.
Has the fund outgrown the universe it invests in — and did size buy a lower fee?
Why this might matterSize narrows what the manager can meaningfully hold and should lower what the investor pays. Read the AUM history beside the expense ratio: a fund that has tripled through inflows while its Regular-plan TER sits above the category median has kept the benefit of scale for the house. The flow decomposition says how much of the growth was money arriving rather than the portfolio compounding.
Why it might notScale funds research teams, and plenty of large funds have gone on compounding for decades. Inflows follow performance, so a fund growing fast is usually one that did well; the constraint is real but not automatically binding, and a TER is a ceiling the AMC can cut at any time.
P7Whose record is thisheadline and record disagree
Run by Jitendra Tolani for 1.5 yrs
What this means. How long the people running it now have been running it, read from the monthly factsheets. A five-year record earned under someone else is not evidence about these managers.
1.5 yrs · Jitendra Tolani
newest teamlongest-serving
50th percentile · above median of 123 funds · category median 1.5 yrs
running it nowJitendra Tolani (since Feb 2025)share of the fund's life under the longest-serving current manager9%changes of hands in the archive2 — last Apr 2025
Who ran it, month by month · factsheets through Sep 2026
* dated by first appearance in the archive we hold, not by a date the factsheet printed. Co-managed months count for every manager named; a factsheet names the manager of record, not who made each call. All managers →
The 5-year record predates everyone currently running it. The longest-serving manager on this scheme has been in place about 1.6 years, against a 5-year figure on display. Jitendra Tolani joined roughly 1.6 years ago. A record earned under different people is not evidence about these ones.
How it is measured, and the case against
A record earned under different people is not evidence about these ones.
Does the displayed record predate the people running it?
Why this might matterA five-year figure on a fund whose longest-serving manager joined two years ago is the house's record more than the person's. The tenure here comes from what each monthly factsheet named, so a change of hands is dated to the month it was disclosed, and the fund's return against its category can be read over exactly those months.
Why it might notFund houses have processes, research desks and mandates that outlast individuals, so a manager change is not a reset. It does mean the displayed record is the house’s more than the person’s.
Tracking gap
the NAV the fund published, against the NAV its last disclosed portfolio would have produced at each day's prices
No signal. Replication needs a fully disclosed domestic-equity portfolio and daily prices for every line; this fund has not been replicated in this build.
Share classes
latest NAV per AMFI code
Plan
Option
NAV
Date
regular Nippon India ETF Nifty Infrastructure BeES
—
₹937.46
21 Sep 2026
The Direct / Regular gap, in rupees
This fund does not have both a Direct and a Regular growth class in the data, so the gap cannot be measured.
A Regular plan buys advice. The fee is visible and the behavioural saving is not; both are shown, neither is netted off.