Concentrated vs Diversified PMS: The Real Risk-Return Tradeoff

At its simplest, concentration in a PMS portfolio is a question of how many stocks it holds and how unevenly the money is spread across them. Based on a review of strategy disclosures and industry commentary across major Indian PMS providers, concentrated PMS strategies commonly hold in the range of 15 to 30 stocks, often with the top five to ten positions accounting for the bulk of the portfolio's value. Diversified or multi-cap PMS strategies, by contrast, frequently run 40 to 50 names or more — spreading position sizes more evenly across sectors and market caps, in an approach one Indian PMS research platform bluntly described as functioning "like a semi mutual fund."

It's worth being precise about what PMS actually is before going further: it's a SEBI-regulated investment vehicle in which a registered portfolio manager builds and manages a portfolio of direct equities inside the investor's own demat account — not a pooled structure like a mutual fund. The current minimum investment is ₹50 lakh, mandated under the SEBI (Portfolio Managers) Regulations, 2020.

Raw stock count is a useful shorthand, but it's a blunt one. A portfolio of 18 stocks where the single largest holding is 25% of assets is meaningfully more concentrated — and riskier in a stock-specific sense — than an 18-stock portfolio where each position is weighted close to 5–6%. A comprehensive academic literature review published in the Journal of Risk and Financial Management makes the point even more sharply: it finds that "a generalized optimal number of stocks that constitute a well-diversified portfolio does not exist for whichever market, period or investor" — the right number depends on correlation structures, the investor's own risk preferences, and whether you're measuring in calm markets or stress periods. That's a useful dose of humility before anyone hands you a hard rule.

The theoretical case for diversification has a precise origin point: economist Harry Markowitz's 1952 paper, "Portfolio Selection," which became the foundation of Modern Portfolio Theory. Markowitz showed, mathematically, that combining assets whose returns don't move in perfect lockstep can reduce a portfolio's overall risk without giving up a proportional amount of expected return — a genuinely novel idea at the time, and one that eventually contributed to Markowitz sharing the 1990 Nobel Memorial Prize in Economic Sciences for this and related work.

But a parallel, older, and equally influential tradition argues the opposite: that true outperformance comes from concentrating capital in your best few ideas rather than diluting it across dozens of average ones. No one has stated the concentrated case more bluntly than Warren Buffett, whose own portfolio at Berkshire Hathaway is a real-world illustration of the philosophy: "diversification is for those who don't know what they're doing."

In India, this decades-old theoretical tug-of-war found a very concrete home once SEBI built out a formal regulatory structure for Portfolio Management Services. The minimum investment for PMS has risen steadily as SEBI has repositioned the product for sophisticated investors: it started at ₹5 lakh when PMS regulations were first introduced in 1993, rose to ₹25 lakh in 2012, and was doubled again to the current ₹50 lakh under the SEBI (Portfolio Managers) Regulations, 2020, which also raised the minimum net worth required of a portfolio manager from ₹2 crore to ₹5 crore. Notably, while these regulations are detailed on manager eligibility, client disclosures, and fees, they do not prescribe a minimum or maximum stock count or sector-concentration limit for a PMS portfolio — unlike the categorization rules SEBI applies to mutual fund schemes. That single regulatory gap is precisely what keeps the concentration-versus-diversification decision alive as a genuine, manager-by-manager choice in the Indian PMS industry, rather than something SEBI has already settled for you.

Two shifts have changed how investors actually engage with this decision in practice, rather than just in theory.

The first is disclosure standardization. Portfolio manager reporting requirements moved to quarterly disclosure under the 2020 regulations, meaning holdings, concentration levels, and performance are now available in structured, comparable form — a prerequisite for any real analysis to happen at all. Before that, an investor comparing two PMS strategies was often comparing two differently-formatted PDFs by hand.

The second is AI-assisted portfolio analysis. Where figuring out exactly how concentrated a given PMS strategy really was — or whether it overlapped heavily with stocks an investor already held elsewhere — used to require manually cross-referencing multiple factsheets, AI-powered comparison platforms now do this automatically: scoring strategies, flagging sector and stock overlap against an investor's existing portfolio, and matching strategies to a stated risk profile in minutes rather than days. That shift matters because concentration is easy to state as a single number — "15 stocks" or "45 stocks" — but genuinely hard to evaluate as a risk without tooling that can compare it against real alternatives and against what an investor already owns.

The return case for concentration is straightforward: when a manager's highest-conviction ideas aren't diluted by dozens of smaller, lower-conviction positions, those best ideas matter more to the final outcome. It's the same logic that shows up, at an extreme, in Warren Buffett's own publicly disclosed equity portfolio at Berkshire Hathaway. As of the most recently reported quarter, Berkshire's top five holdings — Apple, American Express, Coca-Cola, Bank of America, and Chevron — made up roughly 67% of its entire disclosed equity portfolio's value, and its top ten holdings accounted for about 90%, according to Kiplinger's analysis of Berkshire's public filings. Berkshire isn't a PMS and operates at a completely different scale, but it's the clearest real-world illustration of the concentrated-conviction philosophy in action: a small number of deeply understood bets, allowed to compound without being watered down.

The risk side of that same coin is just as real. With fewer holdings, any single stock's stumble has an outsized effect on total portfolio returns — this is what regulators generally call concentration risk, the danger of having too much exposure tied to the fate of one company or sector. Because PMS carries no regulatory cap on single-stock or sector weight the way mutual fund categories do, a concentrated PMS strategy's drawdown during a bad stretch for even one or two holdings can be sharp. This isn't a new observation: the historical "rule of thumb" that a portfolio of just 8 to 10 stocks was sufficiently diversified goes back to a 1968 study by Evans and Archer, but more recent academic work has pushed back on that figure substantially, arguing that today's markets — with different correlation structures than existed decades ago — often require considerably more names to achieve the same risk reduction, per the literature review in the Journal of Risk and Financial Management. In other words: a "concentrated" 15–20 stock PMS portfolio is making a real, measurable bet that idiosyncratic stock-specific risk is a price worth paying for return potential — not a free lunch.

Diversified or multi-cap PMS strategies flip that trade-off. By spreading capital across 40 to 50 or more stocks, the damage any single holding can do to the overall portfolio shrinks proportionally — a stock that halves in value simply matters less when it's one of fifty positions than when it's one of fifteen. That's the entire mathematical promise of Markowitz-style diversification, and it's real.

The cost of that smoother ride is equally real: the more names a portfolio holds, the more its return profile mathematically has to converge toward the broader market or benchmark, since no single high-conviction idea can move the needle much on its own. Pushed far enough, a "diversified" PMS strategy risks drifting into what is sometimes called closet indexing — charging active-management fees for what increasingly resembles benchmark-like performance. Academic estimates of exactly how many holdings are "enough" vary widely by market: some research suggests 30 to 50, or even 100+ stocks for maximum diversification benefit in large, developed markets, while narrower, less liquid emerging markets — arguably closer to segments of the Indian market — may need proportionally fewer names, with some studies putting the figure at roughly 10 to 33 stocks depending on the confidence level targeted. A 40–50 stock "diversified" PMS strategy, in other words, may already sit close to where the diversification benefit curve starts to flatten out.

• Higher alpha potential. When a manager's highest-conviction calls play out, returns aren't diluted by dozens of lower-conviction positions sitting alongside them.
• Capital efficiency. Every rupee is deployed behind an idea the manager has genuinely researched and believes in, rather than spread thin to hit a diversification target.
• Clearer accountability. With a smaller, better-understood set of holdings, it's easier for both the manager and the investor to articulate exactly why each position is in the portfolio.
• Faster expression of new conviction. A manager who identifies a strong new opportunity can size it meaningfully without having to trim twenty other positions first.
• Direct, customizable ownership. Like all PMS (concentrated or not), holdings sit in the investor's own demat account, allowing for stock or sector exclusions that pooled mutual fund units don't permit.

• Lower single-stock drawdown risk. No individual holding is large enough to meaningfully damage the whole portfolio if it disappoints.
• More resilience across market cycles. Spreading exposure across sectors and market caps reduces vulnerability to any one theme or cycle falling out of favor.
• Easier to hold through volatility. Psychologically, it's simpler for many investors to sit through a correction when no single stock dominates the portfolio's story.
• Better suited to larger absolute corpora. For investors deploying a very large sum through PMS, spreading it across more names can keep position sizes at a comfortable rupee amount even at scale.

No matter which side of the concentration spectrum a PMS strategy sits on, a few costs and constraints apply to the category as a whole, and any credible comparison has to be upfront about them.

The most obvious is the entry barrier: the SEBI-mandated ₹50 lakh minimum investment (raised from ₹25 lakh in 2020) puts PMS out of reach for most retail investors, and by design concentrates an investor's exposure in a single manager's judgment. There's also no regulatory diversification floor — because SEBI's PMS regulations don't prescribe stock-count or sector limits, investors have to do their own diligence on how concentrated (or diversified) a strategy actually is, rather than relying on a categorization rule the way mutual fund investors can. And performance dispersion is wide: because PMS accounts are typically built individually rather than drawing on a single pooled track record, two investors in the "same" strategy who joined at different times can see meaningfully different results, which makes short track records especially hard to lean on.

Fees apply regardless of how concentrated the strategy is: management fees typically run 1–2.5% of assets under management annually, plus a performance fee — commonly 10–20% of profits above an agreed hurdle rate, on top of a regulatory framework that bans upfront fees and requires managers to charge only agreed, disclosed fees rather than guaranteeing returns. Because concentrated strategies can also involve more active rebalancing as high-conviction positions are trimmed or added, they can generate more frequent short-term capital gains than a lower-turnover diversified book. Under current Indian tax rules, short-term capital gains on listed equity are taxed at 20% under Section 111A, while long-term capital gains are taxed at 12.5%, with the first ₹1.25 lakh of gains in a financial year exempt, under Section 112A — both rates effective from the Budget 2024 changes of July 23, 2024, which also removed indexation benefits on most such gains. A higher-turnover concentrated strategy doesn't automatically mean a worse after-tax outcome, but it's a real variable that a pure pre-tax return comparison misses.

This is exactly the kind of decision that looks simple from the outside — "concentrated or diversified?" — and turns out to be genuinely hard to evaluate from the inside, because the information that actually matters (real stock-level overlap, true position-weighted concentration, how a strategy behaved in past drawdowns) is scattered across factsheets that aren't built for comparison. Hard-earned wealth shouldn't rely on random advice, and it shouldn't have to rely on manually reconciling PDFs either.

That's the specific problem PMS Sahi Hai — India's first AI-powered PMS & AIF marketplace — was built to solve. Its AI Wealth Compass, Nyra, evaluates strategies across 1,000+ tracked PMS and AIF strategies and is specifically built to reveal hidden overlaps, sector concentration, and duplication risk in a portfolio — precisely the kind of position-weighted analysis that a raw stock count can't give you. Instead of taking a strategy's "15 stocks" or "45 stocks" label at face value, Nyra can show what that actually means for a specific investor's existing holdings, risk profile, and goals, then match it against strategies from the hundreds of SEBI-registered managers tracked in PMS Sahi Hai's manager directory.

For investors who are still getting oriented, PMS Sahi Hai's own PMS FAQ resource walks through concentration risk in plain language, and its "What is PMS" primer covers the basics this article assumes readers already know. The point isn't to push everyone toward one end of the concentration spectrum — it's to compare, evaluate, and invest smarter and faster, with the actual data in front of you instead of a stock count on a brochure.

Rather than asking "which one performs better" — a question with no stable answer, since it flips depending on the market cycle you measure — it's more useful to run through a short set of practical questions:

1. What's your genuine volatility tolerance? Can you watch a single holding fall sharply without feeling compelled to call your manager or exit the strategy at the worst possible time?
2. What does this investment represent as a share of your total net worth? ₹50 lakh in a concentrated strategy means something very different to someone whose total investible assets are ₹1 crore than to someone whose are ₹20 crore.
3. Do you already carry concentrated exposure elsewhere? Large ESOP holdings, a family business stake, or an existing chunky direct-equity position can mean a "diversified" PMS is actually the better complement — or that a concentrated one would dangerously stack risk on risk.
4. What's your investment horizon? High-conviction ideas in a concentrated portfolio may need real time to play out; a shorter horizon generally argues for a smoother, more diversified ride.
5. How will you actually behave in a drawdown? This is less about risk tolerance on paper and more about honest self-assessment — some investors are genuinely fine watching a concentrated position halve temporarily; many only think they are, until it happens.

None of these questions has a universally correct answer — they're inputs into a decision that's specific to one investor's balance sheet, temperament, and goals, which is precisely why a strategy's trailing return alone is such an incomplete way to choose between the two.

Neither a concentrated PMS nor a diversified one is objectively "better." One is a deliberate bet on a manager's best ideas, with the volatility that implies; the other is a deliberate trade of some upside for a smoother, more resilient ride. What matters is that the choice is made deliberately — with a clear-eyed view of stock count, position weighting, cost, tax turnover, and how it sits alongside everything else an investor already owns — rather than by simply chasing whichever approach posted the best trailing return last year.

This is exactly why PMS Sahi Hai built Nyra as an AI Wealth Compass rather than another returns leaderboard: the right question was never "which PMS strategy won last year," it's "which risk-return profile actually fits my money." If you're weighing a concentrated strategy against a diversified one, that's a comparison worth running with real data behind it — not just a fact sheet and a hunch.