Tracking Error: What It Is, How to Calculate, Examples, and Factors
Summary:
Tracking error measures how closely a portfolio’s returns follow its benchmark, highlighting the performance differences that may arise due to fees, investment decisions, or other factors. In this article, we’ll explore what tracking error is, how to calculate it, the factors that affect it, and its implications for investors. We’ll also break down the differences between ex-post and ex-ante tracking errors, give practical examples, and look at tools investors can use to monitor and manage tracking error.
What is tracking error?
Understanding tracking error
Tracking error refers to the difference between the performance of an investment portfolio and its benchmark index. This metric is crucial for investors in mutual funds, exchange-traded funds (ETFs), or hedge funds aiming to replicate or outperform a specific benchmark. The tracking error is typically measured as the standard deviation of these differences over a given time period, often reported as a percentage.
Tracking error shows how consistently a portfolio tracks its benchmark. A low tracking error means the portfolio follows the benchmark closely, while a high tracking error suggests significant deviations from the benchmark. This concept is important for investors, particularly in passive strategies where the goal is to mirror the benchmark’s performance as accurately as possible.
Why is tracking error important?
Tracking error helps investors assess the quality of a portfolio manager’s performance in maintaining a fund’s alignment with its benchmark. If the goal is to replicate the benchmark (such as in index funds), a high tracking error could indicate poor management, unanticipated fees, or other issues. On the other hand, in actively managed funds, a higher tracking error may signal that the fund is taking more risks, which could lead to higher returns—or higher losses.
For institutional investors and individuals alike, tracking error is a tool for evaluating risk management and performance relative to expectations. Understanding and monitoring tracking error can prevent underperforming investments from derailing overall financial goals.
How to calculate tracking error
The tracking error formula
Tracking error is calculated as the standard deviation of the differences between the returns of a portfolio and its benchmark. The formula is expressed as:
To calculate the tracking error:
1. Collect the returns of the portfolio and its benchmark for each period.
2. Calculate the differences between the portfolio returns and the benchmark returns.
3. Find the standard deviation of these differences.
2. Calculate the differences between the portfolio returns and the benchmark returns.
3. Find the standard deviation of these differences.
For example, if a portfolio and its benchmark realized the following returns over a five-year period:
– Portfolio: 11%, 3%, 12%, 14%, 8%
– Benchmark (S&P 500): 12%, 5%, 13%, 9%, 7%
– Benchmark (S&P 500): 12%, 5%, 13%, 9%, 7%
The differences in returns are: -1%, -2%, -1%, 5%, and 1%. Calculating the standard deviation of these differences gives a tracking error of 2.50%. This value shows how much the portfolio’s returns deviated from its benchmark during the observed period.
Ex-post vs. ex-ante tracking error
There are two main types of tracking errors: ex-post and ex-ante.
Ex-post tracking error (realized tracking error) is a backward-looking measure based on historical performance. It calculates how much a portfolio has deviated from its benchmark over a specific period in the past, making it useful for performance evaluation.
Ex-ante tracking error, on the other hand, is forward-looking and estimates how much the portfolio might deviate from its benchmark in the future. This measure relies on risk models, factor analysis, and the portfolio’s current composition. Ex-ante tracking error is essential for risk management and portfolio construction.
While ex-post tracking error provides an accurate reflection of past performance, ex-ante tracking error helps investors forecast future deviations, enabling better-informed decisions regarding portfolio adjustments and risk management.
Pros and cons of tracking errors
Factors affecting tracking error
Fund fees and expenses
One of the most significant contributors to tracking error is the expense ratio of a fund. Indexes themselves do not have expenses, but index-tracking funds like ETFs and mutual funds incur costs such as management fees, operational costs, and taxes. As a result, funds naturally tend to underperform their benchmarks unless the fund manager can add value through superior stock selection, effective rebalancing, or securities lending.
A higher management expense ratio (MER) will typically result in a higher tracking error, particularly in index funds or ETFs where minimizing the difference from the benchmark is a key goal.
Portfolio composition
How closely a fund’s holdings match the benchmark’s holdings can also lead to tracking errors. Index funds may only hold a subset of the securities in the index (known as sampling) to avoid illiquid or thinly-traded securities. These differences in holdings lead to differences in performance, particularly in volatile markets or for funds that track niche or international indexes.
Cash drag
Unlike indexes, funds hold cash to manage transactions, dividends, or interest payments. This cash drag can reduce the fund’s returns compared to its benchmark, especially in periods when the benchmark is rising. Funds with high dividend yields or actively managed cash positions may see more significant cash drag, increasing their tracking error.
Rebalancing and corporate actions
Indexes update their composition regularly based on rules, adding or removing securities. When an index changes, the funds tracking it must rebalance their portfolios to match the new composition. These transactions incur costs and can result in timing mismatches, leading to a temporary tracking error. Additionally, corporate actions like mergers or spin-offs can also contribute to tracking error if funds react differently than the benchmark.
Currency fluctuations and hedging costs
For international funds, currency fluctuations can lead to significant tracking errors. Some ETFs use currency hedging to mitigate the risk of exchange rate volatility, but these hedging strategies come with costs. These additional expenses, and the inherent uncertainties of currency markets, can cause deviations from the benchmark, especially during periods of high volatility.
Premiums, discounts, and liquidity issues
Impact of premiums and discounts
In the case of ETFs, tracking error can arise when the market price of an ETF deviates from its net asset value (NAV). Premiums and discounts happen when investor demand drives the ETF’s market price above or below the value of its underlying assets. Although authorized participants can arbitrage away large premiums or discounts, minor differences between an ETF’s NAV and its market price can persist and contribute to tracking error.
Liquidity and thinly traded securities
Illiquid or thinly traded securities within a fund can increase tracking error due to larger bid-ask spreads. If the securities are not frequently traded, the price at which the fund buys or sells may differ from the market price, causing discrepancies in performance relative to the benchmark.
Tracking error in different types of funds
Sector and international ETFs
Tracking error tends to be higher for sector-specific or international ETFs compared to broad-based equity or bond ETFs. This is because sector ETFs often track benchmarks with concentrated holdings in a few dominant companies, making it harder for fund managers to replicate these indexes within regulatory constraints.
International ETFs face additional challenges, such as currency risks and illiquid foreign markets, which can further increase tracking error.
Dividend and leveraged funds
Dividend-focused ETFs and funds can have significant tracking errors due to the cash drag effect of dividend reinvestments. Additionally, leveraged and inverse ETFs, which use derivatives to amplify or inverse the performance of a benchmark, often experience larger tracking errors because of the complexity of maintaining constant leverage and the cost of derivatives.
Tools to monitor tracking error
Basic tools for retail investors
Retail investors can calculate tracking error using basic tools like Microsoft Excel or Google Sheets. By manually inputting portfolio and benchmark returns, investors can calculate the differences and the standard deviation, giving them a basic tracking error figure. These tools work well for individuals who want to analyze their investments periodically.
Advanced tools for professional investors
For more sophisticated investors or portfolio managers, financial software such as Morningstar Direct or Bloomberg Terminal offers advanced tracking error analytics. These platforms can automatically pull in data, generate real-time tracking error figures, and integrate the results into broader risk management strategies.
Institutional investors often rely on advanced platforms such as BlackRock’s Aladdin, MSCI Barra, or Axioma. These systems not only track tracking error but also offer detailed risk modeling, allowing portfolio managers to make informed adjustments to minimize deviations from the benchmark.
Example of tracking error
Consider an ETF tracking the S&P 500 index. Over five years, the ETF produced returns of 11%, 3%, 12%, 14%, and 8%, while the S&P 500 index had returns of 12%, 5%, 13%, 9%, and 7%. The differences between the ETF and the index are -1%, -2%, -1%, 5%, and 1%. The standard deviation of these differences, the tracking error, is calculated to be 2.50%. This shows how much the ETF’s returns deviated from the benchmark, indicating how well the ETF tracked its index over time.
Conclusion
Tracking error is a key metric for investors seeking to understand how well a portfolio follows its benchmark. By measuring the difference between a portfolio’s returns and those of its benchmark, tracking error helps investors assess the consistency of a fund’s performance. Whether you’re evaluating a passive index fund or an actively managed portfolio, understanding the factors that contribute to tracking error, such as fund fees, portfolio composition, and cash drag, is essential.
A low tracking error suggests that a fund closely follows its benchmark, ideal for passive strategies, while a higher tracking error in active funds could indicate riskier investment choices. By regularly monitoring tracking error, investors can make informed decisions that align with their financial goals and risk tolerance. Whether you are using basic tools like spreadsheets or advanced platforms, tracking error remains a valuable tool for portfolio analysis and performance evaluation.
Frequently asked questions
What causes tracking error in index funds?
Tracking error in index funds is primarily caused by factors such as fund fees, differences in portfolio composition, cash drag, and rebalancing discrepancies. Management expense ratios (MER), transaction costs, and even the timing of dividend reinvestments can contribute to deviations from the benchmark, leading to a higher tracking error.
How is tracking error different from alpha?
Tracking error measures the deviation between a portfolio’s returns and its benchmark, while alpha measures a portfolio’s excess return relative to the benchmark. While tracking error focuses on the consistency of returns, alpha evaluates the portfolio’s ability to generate value beyond what is expected based on market performance.
Can tracking error be used to predict future performance?
Tracking error, particularly ex-ante tracking error, can be used as a tool to estimate future performance deviations based on current portfolio characteristics and risk models. However, it is not a guarantee of future performance. Ex-ante tracking error gives an idea of how much a portfolio might deviate from its benchmark but does not predict whether the deviation will be positive or negative.
How does tracking error affect passive vs. active funds?
For passive funds like index funds and ETFs, a low tracking error is desirable, as it indicates that the fund is closely following the benchmark. For active funds, a higher tracking error may be acceptable or even expected, as the fund manager is intentionally diverging from the benchmark in pursuit of higher returns.
How can investors reduce tracking error in their portfolios?
Investors can reduce tracking error by selecting funds with lower management expense ratios (MER) and closely matching portfolio holdings to the benchmark. Diversification, minimizing transaction costs, and managing cash drag through effective dividend reinvestment are additional strategies to reduce tracking error.
What is a good tracking error for ETFs?
A “good” tracking error for ETFs depends on the fund’s goals. For broad-market index funds, a tracking error under 1% is generally considered acceptable. For sector or international funds, a tracking error of 2% to 5% may be more typical due to the added complexities of tracking those benchmarks.
Can a high tracking error indicate potential returns?
While a high tracking error often reflects significant deviations from a benchmark, it doesn’t necessarily indicate potential returns. In actively managed funds, a high tracking error may suggest that the manager is taking more risks, which could lead to either higher returns or larger losses. The key is evaluating whether the risks taken are aligned with the investor’s goals.
Key takeaways
- Tracking error measures the difference between a portfolio’s returns and its benchmark.
- Lower tracking errors indicate better benchmark replication, while higher errors suggest deviations.
- Common causes of tracking error include fund fees, portfolio composition, cash drag, and rebalancing.
- Both ex-post (historical) and ex-ante (future) tracking errors provide insights into portfolio performance and risk management.
- Tools like Excel, Bloomberg Terminal, and advanced software solutions help monitor tracking error.
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