Sampling is an investment strategy where ETFs or index funds track a benchmark by holding only a representative selection of securities instead of every asset in the index. It is commonly used when full replication would be too expensive, complex, or inefficient, especially in large bond and global index ETFs.
What Is Sampling in Investing?
Sampling is a portfolio management technique where an ETF or index fund holds only a portion of the securities inside a benchmark index while still trying to closely match its overall performance.
Instead of buying every stock or bond in the index, the fund manager selects a representative sample that reflects the index’s:
- Sector exposure
- Geographic allocation
- Credit quality
- Duration
- Market capitalisation
- Risk profile
The goal is to achieve performance that behaves similarly to the benchmark without needing to fully replicate it.
Sampling exists because some indices are extremely large or difficult to replicate efficiently.
For example:
- Global bond indices may contain thousands of bonds
- Corporate bond markets can be illiquid
- Some securities trade infrequently
- Transaction costs can become very high
In these cases, buying every single security may not provide enough additional accuracy to justify the extra costs.
Sampling is especially common in:
- Bond ETFs
- Global equity ETFs
- ESG ETFs
- Multi-factor ETFs
- Broad international indices
How Does Sampling Work?
Here’s the simplified process step by step.
Step 1: The Fund Identifies the Benchmark
The ETF first selects the index it wants to track.
For example:
- Bloomberg Global Aggregate Bond Index
- MSCI World Index
- FTSE Emerging Markets Index
Step 2: The Fund Analyses the Index
The portfolio manager studies the characteristics of the index, including:
- Sector weights
- Country exposure
- Credit ratings
- Maturity profiles
- Company size
- Volatility
The goal is to understand what drives the index’s behaviour.
Step 3: The Fund Selects Representative Securities
Instead of buying every asset, the ETF buys a carefully selected sample that aims to reflect the overall characteristics of the benchmark.
Many ETF providers use quantitative optimisation models to construct representative samples.
For example, a bond ETF tracking an index with 10,000 bonds might only hold 1,000–2,000 representative bonds.
The selected holdings are chosen to behave similarly to the broader index under different market conditions.
Step 4: The Portfolio Is Regularly Adjusted
The ETF continuously monitors performance and risk exposure.
If the sample begins drifting too far from the benchmark, the manager may rebalance the portfolio by adding or removing securities.
The objective is to keep tracking difference relatively low while controlling costs and maintaining liquidity.
Frequent index changes or portfolio adjustments may increase transaction costs and portfolio turnover.
Example of Sampling
Imagine a European ETF provider wants to launch a UCITS ETF tracking a global corporate bond index containing over 15,000 individual bonds.
Buying every bond would create several problems:
- Some bonds rarely trade
- Transaction costs would be high
- Liquidity could be limited
- Portfolio management would become more complex
Instead, the ETF manager uses sampling.
The fund might purchase a representative subset of bonds across:
- Different maturities
- Credit ratings
- Sectors
- Geographic regions
As a result, the ETF can behave similarly to the benchmark without needing to hold every single bond in the index.
This approach is widely used in European bond ETFs because bond markets are often less liquid and more fragmented than stock markets.
Bond pricing can sometimes be less transparent than equity pricing because many bonds trade over-the-counter rather than on centralised exchanges.
Pros and Cons of Sampling
Pros
- Reduces transaction costs
- Improves liquidity management
- More practical for large indices
- Helps manage illiquid securities
- Can improve operational efficiency
Cons
- May increase tracking difference
- Performance may deviate slightly from the benchmark
- Portfolio construction becomes more complex
- Investors may not fully understand the methodology
- Sampling effectiveness depends on portfolio construction models, market conditions, and portfolio-management execution
When Is Sampling Used?
Sampling is most commonly used when full replication is difficult or inefficient.
Examples include:
- Large bond indices
- Global fixed-income ETFs
- Broad international indices
- Illiquid markets
- ESG and thematic indices with frequent rebalancing
For smaller or highly liquid equity indices, many ETFs still use full physical replication because it is simpler and can produce very precise tracking.
However, for large fixed-income markets, sampling is often considered the most practical approach.
European Context
Sampling is widely used in Europe, particularly within UCITS ETFs.
UCITS regulation allows ETF providers to use sampling techniques as long as the fund’s structure, risk management, and disclosures comply with European investor-protection standards.
European ETF providers commonly disclose whether they use:
- Full replication
- Optimised sampling
- Synthetic replication
This information is usually available in the ETF’s:
- Key Information Document (KID)
- Factsheet
- Prospectus
Sampling is especially important in European bond ETFs because European fixed-income markets can be fragmented across:
- Governments
- Corporations
- Currencies
- Credit qualities
- Maturity structures
European investors should also understand that sampling can influence:
- Tracking difference
- Trading spreads
- Liquidity
- Portfolio turnover
Two sampled ETFs tracking the same index may still produce different tracking differences depending on methodology and implementation.
Transparency standards can vary between ETF providers and index methodologies.
Major European ETF providers using sampling techniques include:
- iShares
- Vanguard
- Amundi
- Xtrackers
- SPDR
Related Concepts
- Full Replication — A strategy where an ETF directly owns all securities inside the benchmark index
- Synthetic Replication — A replication method using derivatives such as swap agreements instead of directly owning assets
- Tracking Difference — The difference between an ETF’s actual return and the return of its benchmark index after fees and costs
- Bond ETF — An ETF that invests in government bonds, corporate bonds, or other fixed-income securities
- Index Fund — An investment fund designed to track the performance of a market index
FAQ
Sampling is a strategy where an ETF or index fund holds only a representative selection of securities from an index instead of buying every asset in the benchmark. The goal is to achieve similar performance while reducing costs and complexity.
ETFs often use sampling when an index contains thousands of securities or illiquid assets. Sampling can reduce trading costs, improve liquidity management, and make large bond or global indices easier to track.
Yes, sampling is especially common in bond ETFs because bond indices can contain thousands of bonds that may trade infrequently or have limited liquidity.
Sampling can increase tracking difference slightly because the ETF does not hold every security in the benchmark. However, managers aim to keep performance closely aligned with the index through portfolio optimisation.
Full replication means the ETF owns all securities in the index, while sampling means the ETF holds only a representative subset designed to behave similarly to the benchmark.
This content is for general educational purposes only and does not constitute investment, tax, or legal advice. Investment outcomes and tax treatment depend on individual circumstances and country-specific rules.
Sources
- European Securities and Markets Authority – MiFID II investor-protection rules, fund disclosure standards, and best execution requirements in EU financial markets
- European Commission – UCITS framework, PRIIPs regulation, and Key Information Document (KID) requirements for retail investment products in the European Union
- European Central Bank – Interest rates, inflation, and long-term effects of costs and compounding on investment outcomes
- CFA Institute – Investment fund costs, portfolio construction, passive investing, and long-term investing principles
- Academic finance research (various journals) – Evidence on fund expenses, compounding effects, active vs passive investing, tracking difference, and long-term investor returns
- ETF issuer educational materials (various providers) – Information on accumulating vs distributing ETFs, UCITS fund structures, synthetic replication methods, and ETF domicile considerations
Iva Buće is a Master of Economics specializing in digital marketing and logistics. She combines analytical thinking with creativity to make financial and investment topics accessible to a broader audience. At Finorum, she focuses on translating complex economic concepts into clear, practical insights for everyday readers and investors.
Sources & References
EU regulations & taxation
- European Commission / Taxation & Customs — Interest rates, inflation, and long-term effects of costs and compounding on investment outcomes
- MiFID II investor-protection rules, fund disclosure standards, and best execution requirements in EU financial markets
- UCITS framework, PRIIPs regulation, and Key Information Document (KID) requirements for retail investment products in the European Union