How to Measure Portfolio Concentration Risk: A Practical Framework for Indian Investors

Concentration Is Not the Same as a Small Stock Count

Concentration has several dimensions. Stock count observes only one of them.

Why Concentration Risk Matters

SEBI's investor education guidance describes diversification across securities and asset classes as a way to reduce the negative impact of individual risks, while noting that broad market risk cannot be diversified away. SEBI materials also describe concentration risk as the possibility of significant loss from heavy exposure to a particular security or sector.

A concentrated portfolio can produce exceptional results when its largest decisions are correct. It can also suffer:

• permanent capital loss from one governance or balance-sheet failure;
• large drawdown from a sector cycle;
• forced selling because an illiquid position cannot be reduced gradually;
• unexpected overlap across funds and direct stocks;
• behavioural stress that causes abandonment of the entire strategy;
• family-wealth damage when employment and investments share one risk.

Concentration is not automatically wrong. Unmeasured concentration is the problem.

Bull Run's Five-Lens Concentration Map

Metric 1: Maximum Single-Stock Weight

Use current market value, not invested cost. The maximum weight identifies the portfolio's largest company-specific dependency.

These are diagnostic ranges, not universal recommendations. A stable liquid company and an illiquid leveraged small cap do not represent equal risk at the same weight.

Metric 2: Top-3, Top-5 and Top-10 Concentration

Top-N measures how dependent the portfolio is on its largest decisions.

Top-N is intuitive and easy to monitor, but it ignores how capital is distributed below the cutoff and whether the largest holdings share a common economic driver.

Worked Example: Same Top Five, Different Risk

Two portfolios both have 45% in their top five holdings.

• Portfolio A owns a bank, pharmaceutical exporter, utility, consumer company and software business.
• Portfolio B owns a bank, NBFC, housing financier, real-estate developer and building-material company.

Top-5 concentration is identical. Portfolio B has much higher credit and property-cycle concentration. Top-N must be combined with a risk-cluster map.

Metric 3: Herfindahl-Hirschman Index

The Herfindahl-Hirschman Index, or HHI, squares each portfolio weight and adds the results. Squaring gives larger positions disproportionately more influence.

Use decimal weights. A 10% position is 0.10, not 10.

For ten equal 10% positions:

For twenty equal 5% positions:

A higher HHI means weights are more concentrated. A lower HHI means capital is more evenly distributed.

Metric 4: Effective Number of Holdings

Effective holdings convert HHI into a stock-count-like number. A portfolio with HHI of 0.10 has an effective count of 10. A portfolio with HHI of 0.05 has an effective count of 20.

This interpretation concerns weights, not independent business risks. Twenty effective holdings inside one sector can still be highly concentrated economically.

Metric 5: Breadth Efficiency

Bull Run's Breadth Efficiency Ratio compares effective holdings with the nominal stock count.

Suppose a portfolio has 25 stocks but an effective count of 10. Breadth efficiency is 40%. Fifteen holdings add names and monitoring work but limited weight diversification.

Worked Example: Calculating HHI

Consider a ten-stock portfolio with weights of 20%, 15%, 12%, 10%, 10%, 8%, 8%, 7%, 5% and 5%.

The portfolio contains ten stocks but has the weight concentration of approximately 8.4 equal positions. Its breadth efficiency is about 84%, meaning the count is broadly representative even though the top position is large.

Metric 6: Sector Concentration

Calculate sector weights at both broad and sub-sector levels. Financial services, for example, can include banks, NBFCs, insurers, housing finance, brokers, exchanges and asset managers. These business models differ, but many share exposure to credit, rates, regulation or market activity.

Broad sectors deserve more room when they contain several independent earnings engines. A narrow commodity or thematic sector deserves a lower maximum than diversified financial services, even at the same headline percentage.

Metric 7: Sector HHI

Sector HHI applies the same squared-weight formula to sector weights.

A portfolio split equally across eight sectors has sector HHI of 0.125 and an effective sector count of 8. A portfolio with 40% financials, 25% technology, 15% consumer and 20% across other sectors has a much lower effective sector count.

Sector HHI is useful for comparing portfolio versions over time. It is less useful when official sector labels hide common economic exposure.

Metric 8: Economic Risk-Cluster Concentration

Group holdings by the event that can damage them together.

One company can belong to several clusters. The objective is not to force exposures to sum to 100%. It is to identify common failure channels.

Gross Cluster Exposure vs Primary Cluster Exposure

Two methods are useful:

• Primary cluster: assign each holding to the single most important driver, allowing weights to sum to 100%.
• Gross cluster exposure: assign a holding to every material driver, allowing total exposures to exceed 100%.

Primary mapping is easier for dashboards. Gross mapping is better for stress analysis. An airline can be exposed simultaneously to domestic demand, crude oil, currency and regulation.

Metric 9: Portfolio-at-Risk from One Holding

This metric links capital concentration with the severity of failure.

Severe downside should reflect business failure, valuation compression, debt, dilution, liquidity and governance—not a convenient stop-loss percentage.

Metric 10: Cluster Portfolio-at-Risk

Suppose a credit stress scenario affects:

• 10% bank position with 35% downside;
• 6% NBFC position with 55% downside;
• 5% real-estate position with 50% downside;
• 4% auto position with 30% downside.

The portfolio holds four companies across several sectors, but one economic scenario can reduce total value by more than 10% before market-wide effects.

Metric 11: Downside HHI

Traditional HHI uses capital weights. Bull Run's Downside HHI applies HHI to each holding's share of estimated severe portfolio loss.

This answers a different question: how concentrated is the portfolio's estimated severe loss? A 3% illiquid small cap can contribute more downside than a 6% defensive large cap.

Downside HHI is an original diagnostic framework rather than an empirically validated forecasting model. Its usefulness depends entirely on conservative, consistently prepared downside estimates.

Metric 12: Correlation Concentration

Portfolio variance depends on weights, volatility and correlation.

Here, w is the weight vector and Σ is the covariance matrix. A portfolio can have small positions but remain risky when correlations are high.

Correlation must be interpreted cautiously:

• historical relationships can change;
• correlations often rise during stress;
• short data windows can create unstable estimates;
• illiquid prices can understate measured volatility and correlation;
• business exposure may be shared even when past prices did not move together.

Use statistical correlation alongside fundamental cluster mapping, not as a replacement.

Metric 13: Contribution to Portfolio Volatility

For investors with reliable return data, component contribution to risk can estimate which positions drive portfolio volatility.

Contributions should sum to approximately 100%, subject to calculation conventions. A 5% high-volatility, highly correlated stock may contribute more risk than a 10% low-volatility holding.

Volatility contribution is not permanent-loss contribution. A stable share price can hide leverage, accounting risk or illiquidity. Use it as one lens.

Metric 14: Active Share and Benchmark Concentration

Investors comparing an active portfolio with an index can calculate Active Share:

A high Active Share means holdings and weights differ materially from the benchmark. It does not show whether absolute risk is high or low. A portfolio can have low Active Share and still inherit a concentrated benchmark, or high Active Share and remain diversified across independent businesses.

The Nifty 50 is free-float market-cap weighted. As of March 30, 2026, NSE Indices reported that it represented about 53.73% of NSE free-float market capitalisation. A free-float-weighted benchmark naturally allocates more capital to companies with larger investable market values.

Benchmark Weight Is Not a Personal Risk Limit

An index weight reflects index methodology. It does not consider:

• the investor's employment or business exposure;
• financial goals;
• direct-stock conviction;
• tax circumstances;
• liquidity needs;
• ability to research the company;
• the amount held through other funds.

A stock can be a large benchmark constituent and still be too large for one family's financial position.

Metric 15: Look-Through Fund Concentration

Combine exposure across index funds, ETFs, active funds and direct stocks.

Example:

• 50% of equity is in Fund A, which holds 9% in Company X.
• 25% is in Fund B, which holds 6% in Company X.
• 5% is held directly in Company X.

The demat account shows a 5% position. The economic portfolio owns 11%.

Fund Overlap Beyond Exact Stocks

Two funds can own different companies while sharing:

• financial-services exposure;
• large-cap growth;
• mid-cap momentum;
• quality or value factors;
• government-capex exposure;
• domestic consumption;
• small-cap liquidity risk.

Measure exact overlap, then sector, market-cap, factor and risk-cluster overlap.

Metric 16: Liquidity Concentration

Capital concentration becomes more dangerous when the largest positions are difficult to exit.

The 10% participation assumption is illustrative. Smaller participation may be necessary for thin order books.

A two-to-five-times multiplier can be used for scenario analysis rather than prediction.

Lower circuits, wide spreads and disappearing buyers can make realised execution materially worse than the calculation.

Liquidity-Weighted Concentration Map

Sort holdings into four cells:

Metric 17: Personal-Wealth Concentration

The demat account is not the full economic portfolio. Include:

• employer shares and ESOPs;
• salary and bonus dependence on one industry;
• family business;
• unlisted equity;
• property linked to the same local economy;
• loans to one business group;
• retirement funds holding the same securities;
• spouse and family investment overlap.

The non-listed components cannot always be valued precisely. Approximate mapping is still better than ignoring them.

Worked Example: Technology Employee

An investor's listed portfolio has only 15% in technology. However, salary, annual bonus, ESOPs and career prospects all depend on global technology spending. A technology downturn can reduce income and investment value simultaneously.

The personal balance sheet is more concentrated than the portfolio dashboard. The investor may prefer less technology exposure in financial assets even when the benchmark has a significant sector weight.

Metric 18: Revenue and Customer Concentration

Portfolio companies can share one customer, geography or supplier even when they belong to different sectors.

Track:

• percentage of portfolio revenue from the United States, Europe, China or India;
• exposure to one government agency or public-sector customer;
• dependence on automotive, real estate, telecom or banking clients;
• common raw materials and suppliers;
• common currency exposure;
• top-customer concentration inside each company.

A portfolio with several export companies may be geographically concentrated despite sector diversity.

Metric 19: Market-Cap Concentration

Market-cap concentration affects liquidity, business maturity, valuation dispersion and drawdown behaviour.

A 30% small-cap allocation across low-free-float direct holdings is much riskier than the same percentage in liquid large caps.

Metric 20: Factor Concentration

Holdings can share style characteristics:

• high valuation and high growth;
• low valuation and cyclical earnings;
• momentum;
• quality and profitability;
• high dividend yield;
• low volatility;
• small size;
• state ownership;
• high leverage.

A portfolio may own companies from ten sectors but remain concentrated in expensive quality or small-cap momentum. Factor exposure often becomes visible only when the market regime changes.

Metric 21: Thesis Concentration

Thesis concentration occurs when several holdings require the same forecast to be correct.

Examples:

• India's capital-expenditure cycle remains strong;
• interest rates fall and credit growth accelerates;
• premium consumption remains resilient;
• China-plus-one manufacturing gains continue;
• the rupee weakens;
• global technology spending recovers;
• one government policy remains supportive.

Write one sentence for why each holding should succeed. Count repeated assumptions. A portfolio with different businesses but one repeated sentence is concentrated.

Bull Run's Concentration Dashboard

Concentration Action Bands

Bull Run uses a three-level action system:

The system prevents small market movements from causing unnecessary turnover while ensuring serious concentration receives a documented response.

Worked Example 1: Twenty Stocks, Ten Effective Holdings

A portfolio owns 20 stocks. The five largest weights are 15%, 12%, 10%, 8% and 7%. The remaining 48% is spread across fifteen holdings.

The nominal count is 20, but HHI produces an effective count near 10–12 depending on the exact remaining weights. Top-five concentration is 52%. The portfolio should be treated as a focused strategy, not a broad 20-stock portfolio.

Worked Example 2: Equal Weights, One Risk Cluster

A portfolio holds twenty 5% positions, producing an HHI of 0.05 and effective holdings of 20. Ten companies depend directly or indirectly on government capital expenditure.

Weight concentration is low. Economic concentration is high. A capex slowdown can affect half the portfolio. The solution is not necessarily more names; it is more independent earnings drivers.

Worked Example 3: Small Position with Large Downside

A 3% illiquid special situation has an estimated severe downside of 85%.

A 6% liquid defensive stock with 30% severe downside creates only 1.8% portfolio-at-risk. Capital weight alone would identify the second stock as more concentrated; downside concentration identifies the first as more dangerous.

Worked Example 4: Fund Overlap Doubles Exposure

An investor holds one company directly at 6%. Look-through exposure through two funds adds another 5%. Total company exposure is 11%.

A 50% severe decline can reduce total equity by 5.5%. The investor can trim the direct position, change fund structure or consciously accept the concentration after documenting the risk.

Worked Example 5: Sector Diversification, Currency Concentration

A portfolio holds IT services, pharmaceuticals, auto components, specialty chemicals and engineering exporters. Official sector diversification looks strong, but 65% of portfolio revenue is linked to foreign customers and much of the expected margin depends on the rupee.

The portfolio has geographic and currency concentration. Domestic cash-flow exposures may improve resilience more than another export sector.

Worked Example 6: Employer and Portfolio Overlap

An employee of a private bank receives salary, bonus and ESOPs from the same institution and holds bank stocks through funds and direct investments.

A financial-sector stress event can affect employment income, ESOP value and liquid savings together. Personal-wealth concentration is much higher than the demat account suggests.

Worked Example 7: Illiquid Small-Cap Basket

A portfolio owns 25 small caps at 4% each. HHI suggests 25 effective holdings. Several positions require more than ten stressed trading days to exit.

Stock-weight concentration is low, but liquidity concentration is severe. During a broad small-cap correction, the investor may be unable to reduce several holdings simultaneously.

Worked Example 8: One Winner Changes the Portfolio

A 5% position triples while the rest of the portfolio rises 10%. Starting from 100:

• the position grows from 5 to 15;
• the remaining 95 grows to 104.5;
• total becomes 119.5;
• the position becomes approximately 12.6%.

The business may remain excellent. The concentration policy has changed through price movement. A review is required even without a negative thesis.

Worked Example 9: Index Core with Active Satellite

An investor holds 75% in a broad Indian index core and 25% in direct stocks. The direct sleeve concentrates in the same large companies that dominate the core.

The account structure appears core-satellite, but look-through Active Share is low and company concentration rises. Satellites should add a deliberate edge, not merely duplicate familiar benchmark holdings.

Worked Example 10: Concentration Is Intentional

An experienced investor holds twelve companies, 55% in the top five, with deep research, strong liquidity and explicit loss budgets. The investor accepts benchmark deviation and can tolerate a severe drawdown.

The portfolio is concentrated but not accidentally so. Measurement does not require automatic diversification. It ensures the investor understands the consequences and has not confused conviction with certainty.

The Quarterly Concentration Audit

Portfolio Concentration Worksheet

Common Concentration-Measurement Mistakes

1. Counting stocks without measuring weights

A long holdings list can still be dominated by five positions.

2. Using HHI as the only answer

HHI cannot detect common customers, sectors, factors or liquidity.

3. Treating official sectors as independent risks

Credit, capex, currency and commodity shocks cross classifications.

4. Ignoring mutual funds

Direct positions can duplicate large underlying fund holdings.

5. Using historical volatility as permanent-loss risk

Low volatility can coexist with leverage, governance or illiquidity.

6. Using normal trading volume

Liquidity can disappear exactly when a thesis changes.

7. Ignoring personal income

Employment and investments can fail together.

8. Assuming benchmark weight is automatically safe

An index does not know the investor's personal balance sheet.

9. Treating all 10% positions equally

Severe downside and liquidity can differ dramatically.

10. Measuring concentration only after a crisis

Risk limits are most useful before prices and liquidity deteriorate.

How Bull Run Features Fit Concentration Analysis

Use the Bull Run watchlist to keep new ideas outside the portfolio until they improve diversification or expected return. A new ticker should not be purchased merely to increase the stock count.

Use Bull Run Compare to identify duplicated business models, debt profiles, growth drivers and valuations. Comparing holdings competing for the same portfolio role can reveal where one position should replace another rather than coexist.

The Stock Battle tool helps decide which company deserves a limited sector or risk-cluster budget. Smart Screeners can identify candidates in underrepresented sectors without forcing immediate allocation.

Primary Official and Research Sources

• SEBI Investor: managing investment risks and diversification
• SEBI Investor: asset allocation, review and rebalancing
• SEBI Investor: concentration and liquidity risks in focused portfolios
• NSE Indices: Nifty 50 free-float methodology and market coverage
• NSE Indices: Nifty 500 market coverage
• Dabi and Dabi: concentration measurement for Indian equity indices
• Kritzman and Turkington: effective holdings and the distinction between holdings concentration and risk
• Raju and Agarwalla: equity portfolio diversification evidence from India
• Ivkovic, Sialm and Weisbenner: concentration and individual investor performance
• Bull Run data sources and coverage policy