Benchmark Selection in PMS: Why the Wrong Benchmark Hides Bad Performance

A benchmark is the yardstick a Portfolio Management Service (PMS) is measured against — typically a published market index that represents the segment of the market the strategy is supposed to operate in. If a PMS returns 18% in a year, that number is meaningless in isolation. Was 18% exceptional, or did the broader market return 22%? Was the risk taken to get there proportionate? The benchmark is what turns a raw return into an answer.

In theory, benchmark selection should be mechanical: match the index to the portfolio. A strategy that invests mostly in the largest, most liquid Indian companies should be measured against a large-cap index. A strategy built around mid-sized, faster-growing companies should be measured against a mid-cap index. In practice, Indian PMS regulation gives providers meaningfully more latitude in this choice than mutual funds get — which is precisely why benchmark selection deserves far more investor attention than it usually receives.

This matters more in PMS than almost anywhere else in Indian investing because of who is investing: PMS has a SEBI-mandated minimum investment of ₹50 lakh, according to Forbes Advisor India, putting it squarely in the territory of high-net-worth individuals, family offices, and NRIs — investors writing large cheques based on a track record that is, in large part, defined by a benchmark comparison.

Benchmarking as a discipline didn't begin with PMS — it began with institutional asset management, where pension funds, endowments, and insurance portfolios needed an objective way to judge whether an external manager was adding value or simply riding the market. A manager who returned 12% when the market returned 15% wasn't a good manager, however large the absolute number looked. This logic — measure everything relative to a passive alternative — eventually filtered down into mutual funds and, later, into India's PMS industry.

Indian mutual funds formalised this early through SEBI's rigid AMFI and SEBI category-benchmark mapping, where a "large-cap fund" is legally defined by market-cap bands and must be benchmarked accordingly. According to Wikipedia's overview of the NIFTY 50, India's flagship index tracks the 50 largest, most liquid companies on the National Stock Exchange — a natural fit for large-cap strategies, but a poor fit for anything smaller.

PMS took a different regulatory path. Because PMS strategies are built around a Portfolio Manager's specific investment philosophy — often concentrated, sometimes thematic, frequently tilted toward mid- and small-caps in pursuit of higher growth — regulators historically left benchmark choice largely to the manager's discretion. That flexibility is not inherently a flaw; concentrated, high-conviction strategies are part of what PMS investors are paying for. But it also meant that, until relatively recently, there was no standardised requirement forcing a manager's chosen benchmark to reflect what the portfolio actually held.

That changed materially with SEBI's December 16, 2022 circular on Performance Benchmarking and Reporting of Performance by Portfolio Managers, effective April 1, 2023 — coverage confirmed at the time by Business Standard. The framework works like this:

• Every Investment Approach (IA) a Portfolio Manager offers must be tagged to exactly one of four strategy categories: Equity, Debt, Hybrid, or Multi-Asset.
• The Association of Portfolio Managers in India (APMI) prescribes a maximum of three approved benchmarks for each strategy category, and the manager selects one from that list — intended, in SEBI's own words, to "reflect the core philosophy of the Strategy."
• Cherry-picked, hand-selected client returns cannot be shown in isolation; disclosure must reflect the entire Investment Approach.
• If a manager changes an IA's benchmark or strategy category, existing clients must be offered an exit option without an exit load — an implicit regulatory acknowledgment that a benchmark change can materially alter what "performance" means to an investor already in the strategy.

SEBI has since folded and updated this framework inside its consolidated Master Circular for Portfolio Managers, issued June 7, 2024, which brought registration, reporting, valuation, and client-disclosure requirements under one reference document, with fee-transparency amendments effective October 1, 2024.

This is genuine progress in investor protection. But notice precisely what the rule does not do: it does not force a mid-cap-heavy strategy into a mid-cap benchmark. It only narrows the manager's choice to a short, APMI-approved list for that strategy's category — and a broad, easier-to-beat index can still legitimately be on that list.

Every PMS performance disclosure built under the current framework leans on two distinct return calculations, and confusing them is one of the most common ways investors misread a fact sheet.

Time-Weighted Rate of Return (TWRR) measures the strategy's performance by removing the distorting effect of when money moved in and out of the portfolio. It answers: "How well did the manager actually invest?" TWRR is the number SEBI requires to be compared directly against the chosen benchmark, because it isolates manager skill from investor timing.

Extended Internal Rate of Return (XIRR), by contrast, is calculated per investor and reflects the actual annualised return you experienced, including the effect of exactly when you invested and how much. SEBI's rules require Portfolio Managers to disclose XIRR alongside the minimum, maximum, and median XIRR across all clients in that Investment Approach — because two investors in the identical strategy can have meaningfully different personal outcomes depending on timing.

The practical implication: a strategy can show a strong TWRR comfortably ahead of its benchmark, while your own XIRR tells a noticeably less flattering story — or vice versa. Always ask which number is being quoted, and against which benchmark the TWRR (not the XIRR) was compared.

Here is the mechanism at the center of this article. Because APMI's approved list still permits a broad, large-cap-anchored index to be chosen for strategies that aren't actually large-cap in composition, a portfolio manager running a mid- or small-cap-heavy book can legally benchmark it against something like the Nifty 50 or a broad 500-stock index rather than a narrower mid-cap or small-cap index.

The Nifty 500, per NSE India's own index page, represents the top 500 companies by full market capitalisation and covers roughly 92% of NSE's free-float market cap — but that weight is still concentrated in India's largest companies, the same way the Nifty 500's broader index construction skews toward large-cap influence even while nominally including smaller names. Comparing a concentrated mid-cap or small-cap PMS strategy against an index this large-cap-influenced sets up a mismatch before a single stock is picked.

This isn't a hypothetical risk. An analysis by Moneycontrol of PMS performance data found:

• Among 22 mid-cap-oriented PMS schemes, 14 beat the broad S&P BSE 500 — but only 6 beat the S&P BSE 150, the index that actually reflects mid-cap performance.
• Among 18 small-cap-oriented PMS schemes, 14 beat the broad index — but only 8 beat the S&P BSE 250, the true small-cap comparison.

Read that again: more than twice as many schemes looked like outperformers against a broad index as against the index that actually matched what they held. Nothing changed about the underlying portfolios. What changed was the yardstick. Mid- and small-cap stocks have historically delivered higher (and more volatile) returns than large-caps over most multi-year periods, so a mid-/small-cap-heavy portfolio measured against a large-cap-anchored benchmark starts with a structural tailwind that has nothing to do with the manager's stock-picking skill.

It's worth being explicit about why this problem is more pronounced in PMS than in mutual funds, because the two are frequently compared by the same HNI and family-office investors deciding where to deploy capital.

Mutual funds operate inside SEBI's strict scheme-categorisation framework: a fund labelled "large-cap" is legally required to hold a defined proportion of assets in the largest companies by market capitalisation, and its benchmark follows automatically from that category. There is very little room for a mutual fund to drift into a different market-cap segment while keeping its original label and an easier benchmark.

PMS has no equivalent market-cap-band mandate. A "Multi Cap" or "Flexi Cap" PMS label describes an intent, not an enforced allocation — a manager can run a portfolio that is 60–70% mid- and small-cap under a label that sounds broader and safer than the holdings actually are. Combine that with a benchmark chosen from a short APMI-approved list rather than one that must exactly mirror portfolio composition, and you get two forms of the same underlying issue: style drift in what the portfolio holds, and benchmark mismatch in what it's compared against.

This is not a case for regulatory alarm — PMS's flexibility is also what allows genuinely differentiated, high-conviction strategies to exist. It is, however, a clear case for investor diligence that goes beyond the label on the fact sheet.

Published performance data adds an important second layer to the benchmark-mismatch story: even when segment-appropriate benchmarks are used, genuine outperformance in PMS is far less common than marketing narratives suggest.

According to Business Standard's analysis of 2022 performance data, 72.6% of 212 PMS schemes analysed (154 schemes) underperformed their own benchmarks that year — meaning only 27.4% of providers beat the index they were actually measured against. The segment breakdown is revealing:

Small-cap was the only segment where a clear majority of schemes beat their benchmark that year — a reminder that outperformance rates swing significantly by market cycle and segment, not just by manager skill. Taken together with the Moneycontrol benchmark-mismatch finding above, the honest picture is this: genuine, correctly-benchmarked outperformance in PMS is inconsistent and segment-dependent, and some of the "outperformance" investors see in marketing material comes from comparing a portfolio against an index it was never really competing with in the first place.

When a benchmark genuinely matches a portfolio's composition, it delivers real value to an investor:

1. Separates skill from beta. A correctly matched benchmark tells you whether outperformance reflects the manager's stock-picking or simply exposure to a segment of the market that happened to do well.
2. Justifies (or exposes) fees. PMS fees frequently exceed 2% of AUM; a fair benchmark tells you whether that fee is buying genuine skill or exposure you could access more cheaply elsewhere.
3. Reveals true risk. A strategy that looks "steady" against a broad, large-cap-anchored index may in fact be far more volatile than its real peer set once measured correctly.
4. Enables cross-portfolio comparison. Investors holding multiple PMS and AIF strategies can only sensibly compare them if each is measured on a comparable, appropriate basis.
5. Builds long-term trust in disclosure. Standardised, correctly-matched TWRR reporting against an appropriate benchmark is auditable — good performance data should hold up under scrutiny, not depend on which index was chosen to display it against.

Honest coverage of this topic requires acknowledging where the current rules still fall short:

1. The approved-list structure permits mismatch. Because APMI prescribes up to three benchmarks per strategy category rather than mandating an exact composition match, a broad, easier-to-beat index can remain a technically compliant choice even for a concentrated, narrower strategy.
2. No enforced market-cap allocation bands. Unlike mutual funds, PMS strategies aren't bound by strict market-cap allocation rules, so a label like "Multi Cap" doesn't guarantee the underlying portfolio matches that description.
3. Attribution data isn't standardised or easy to access. Even a diligent investor typically can't easily see, from a standard PMS fact sheet, how much of a strategy's return came from sector allocation, stock selection, or simply holding a different market-cap mix than the benchmark — the data needed to fully judge "is this real skill?" usually requires asking the manager directly.

Benchmark selection is no longer just a line in a disclosure document — it's a live data problem. Under the current framework, Portfolio Managers must report monthly performance data to APMI and SEBI within seven working days in standardised TWRR/XIRR formats, and valuations must follow APMI-empanelled-agency norms rather than a manager's own methodology.

This standardisation is exactly what makes technology-driven comparison platforms possible. Rather than relying on a fact sheet's self-selected benchmark, a comparison and monitoring layer can pull standardised TWRR data across many Investment Approaches and re-express it against a consistent, portfolio-appropriate benchmark — closing much of the gap that the approved-list system still leaves open. This is precisely the function an AI-driven PMS and AIF marketplace is built to perform, and it's a meaningfully different (and more useful) approach than reading each provider's self-reported comparison in isolation.

Before you treat any "beat the benchmark" headline as evidence of skill, work through this checklist:

1. Look at the actual holdings, not the label. If a strategy is marketed as "Multi Cap" or "Flexi Cap" but holds 60–70% in mid- and small-caps, ask directly why the chosen benchmark doesn't reflect that.
2. Ask which of APMI's approved benchmarks was selected, and why. Managers choose from a short list; a broad, large-cap-tilted choice for a concentrated small-cap book is a fair, direct question to raise.
3. Separate TWRR from XIRR. TWRR tells you how well the manager invested; your personal XIRR (and its spread across the manager's client base) tells you what you're likely to actually experience.
4. Request attribution, not just headline returns. A breakdown of how much outperformance came from sector allocation, stock selection, or simply a different market-cap mix tells you whether you're paying for skill or for a mismatch.
5. Track benchmark or strategy changes over time. If a manager has switched benchmarks, find out when and why — and remember that a benchmark or strategy change entitles you to exit without a load.
6. Compare like-for-like across your full portfolio. If you hold several PMS and AIF strategies, each measured against a different benchmark, true portfolio-level performance is nearly impossible to judge by eye without normalising them onto a common basis.

This is precisely the blind spot Nyra, PMS Sahi Hai's AI Wealth Compass, was built to close. Rather than accepting a Portfolio Manager's self-selected benchmark at face value, Nyra evaluates strategies from PMS Sahi Hai's tracked universe of 1,000+ PMS & AIF strategies on a consistent, comparable basis — so a mid-cap-heavy strategy is judged as a mid-cap-heavy strategy, not flattered by a broad-index comparison chosen for the fact sheet.

Nyra's process starts by understanding your risk appetite, investment horizon, and goals, then analyses your existing portfolio to reveal hidden overlaps, sector concentration, and duplication risk — the same style-drift problem that makes benchmark mismatch possible in the first place. From there, it curates PMS and AIF matches genuinely suited to your profile, rather than ones that simply look best against a favourable index, and continues monitoring your holdings for the sector shifts and liquidity changes that matter long after the initial investment. As a SEBI-registered distributor & advisor, PMS Sahi Hai's role is to make this comparison process transparent for HNIs, NRIs, and family offices — not to take a manager's chosen yardstick as the final word.

If you want to see this in practice on your own portfolio, you can check what PMS actually is and how it's structured before comparing specific strategies through the PMS comparison tool.

Benchmark selection isn't a footnote in a PMS fact sheet — it's the entire basis on which you judge whether a 2%+ fee is buying genuine skill or exposure you could have accessed more cheaply elsewhere. The regulatory framework SEBI and APMI have built since 2022 is real progress, standardising TWRR and XIRR disclosure and narrowing manager discretion to an approved list. But as the data shows, an approved list still leaves room for a benchmark that flatters rather than tests a portfolio.

The remedy isn't to distrust every PMS fact sheet — it's to ask the right questions before you invest, and to compare strategies on a consistent basis rather than taking each provider's self-selected yardstick at face value. That is the exact problem PMS Sahi Hai and Nyra were built to solve: normalising performance across 1,000+ tracked PMS and AIF strategies so you can see genuine skill instead of a favourable benchmark. Hard-earned wealth shouldn't rely on random advice — and it certainly shouldn't rely on a benchmark chosen to make the numbers look better than they are.

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