With the growing popularity of index funds and ETFs, investors aim to achieve returns that align with benchmark indices like the Nifty 50 and Sensex. But how can you assess whether these funds effectively track their benchmarks? The key lies in tracking error, a vital metric that helps measure a fund’s performance in replicating its index. Though it may sound technical, tracking error has a direct impact on investment outcomes. This blog breaks down the concept, explaining its significance, calculation, and its influence on investment strategies. Whether you’re experienced or new to mutual funds, understanding tracking error can offer valuable insights into the performance and suitability of index fund and ETF investments in India.
Table of Contents
What is tracking error?
Tracking error is a measure of the difference in returns of a fund and its benchmark. In the context of an index fund or an exchange traded fund, tracking error indicates how closely your investment matches the target index that it has designed itself on. This can help assess the fund’s performance over time and its relative risk and volatility.
Why does tracking error occur?
Several reasons can contribute to tracking errors:
- Fund expenses: There are charges associated with maintaining a fund, such as management and transaction fees. These expenditures are paid with the fund’s money, which means lower returns.
- Cash balance: Funds may need to keep cash for several reasons, such as investor redemption or Income distribution cum capital withdrawal This cash is not invested in the index, resulting in different returns.
- Corporate actions: Stock splits and mergers compel funds to modify their holdings. These modifications might increase expenses and make it more difficult for the fund to match the index.
Read Also: What is Information Ratio in Mutual Funds?
Importance of tracking error in mutual funds and portfolio management
For those investing in index funds and exchange-traded funds (ETFs) in India, tracking error is an important measure of how well the fund is meeting its objective. A lower tracking error indicates the fund is closely mirroring its benchmark index, offering investors market-aligned performance, while a higher tracking error may mean noticeable differences from the benchmark, which can result in returns that do not meet expectations.
In the context of portfolio management, tracking metric helps investors understand whether the passive component of their allocation is delivering benchmark-like exposure or drifting away from the intended structure.
For example, when an investor allocates a portion of the portfolio to an index fund for relatively predictable benchmark-linked behaviour, a relatively low tracking error helps maintain the overall asset allocation framework. If the tracking error widens, the portfolio may unintentionally take on additional active risk.
Tracking error does not indicate potential future performance, but it provides valuable insight into implementation quality. It supports alignment between the investor’s intended risk profile and the portfolio’s actual behaviour over time.
Formula for tracking error
The commonly used formula for tracking error is:
Tracking error = √[ Σ (Rp − Rb − Average difference)² / (n − 1) ]
Where:
Rp = portfolio return
Rb = benchmark return
n = number of observations
A lower tracking error indicates that the fund’s returns have remained relatively close to its benchmark, while a higher tracking error shows larger deviations.
How to calculate tracking error?
Tracking error is calculated by comparing a fund’s returns with those of its benchmark index over a specific period. Here’s a straightforward method:
- Gather daily or monthly returns of both the fund and the benchmark index for the selected period.
- Compute the difference between the fund’s return and the benchmark’s return for each period.
- Determine the standard deviation of these differences. This standard deviation represents the tracking error.
- Apply the formula.
Example of calculating tracking error
Here’s a hypothetical example: Suppose an index fund tracks the Nifty 50, and the following are its monthly returns over three months:
| Month | Fund Return (%) | Nifty 50 Return (%) | Difference (%) |
| 1 | 2.1 | 2.3 | -0.2 |
| 2 | 1.8 | 1.7 | 0.1 |
| 3 | -0.5 | -0.4 | -0.1 |
Calculate the differences: -0.2, 0.1, -0.1.
Square the differences: 0.04, 0.01, 0.01.
Sum the squared differences: 0.06.
Divide by (n-1): 0.06 / 2 = 0.03.
Take the square root: 0.03 ≈ 0.173.
Therefore, the tracking error for this example is approximately 0.173%, or 17.3 basis points. This means that the fund’s returns have deviated from the Nifty 50’s returns by approximately 17.3 basis points on average per month.
What is a good tracking error?
Determining a suitable tracking error in Indian mutual funds depends on the index fund or ETF and its benchmark. A lower tracking error indicates that the fund’s returns are closely aligned with the benchmark. Funds tracking highly liquid indices like the Nifty 50 or Sensex typically have lower tracking errors than those following less liquid or specialized indices. Instead of focusing on a specific number, it is more useful to compare tracking errors among similar funds. When evaluating index funds, investors should consider tracking error alongside other factors like expense ratios and the fund’s investment objective.
Factors influencing tracking error
Several elements contribute to tracking error in Indian mutual funds:
- Expense ratio: Higher expense ratios reduce fund returns, leading to a greater divergence from the benchmark.
- Cash holdings: Funds may hold some assets in cash, which can result in underperformance during market rallies.
- Sampling techniques: Some funds use sampling instead of holding all index constituents, which may introduce tracking error.
- Regulatory restrictions: Certain investment constraints or regulatory limitations may prevent exact index replication.
- Dividend reinvestment: The timing and method of reinvesting dividends can create small return differences between the fund and its benchmark.
Benefits of tracking error
While minimizing tracking error is generally preferred, understanding it offers several advantages:
- Performance evaluation: It provides a numerical measure of how well a fund tracks its benchmark.
- Fund comparison: Investors can compare similar index funds or ETFs to identify those that more closely follow their benchmarks.
- Risk assessment: It helps gauge the extent of a fund’s deviation from its benchmark.
- Transparency: Tracking error enhances transparency by showing how closely a fund aligns with its stated objective.
- Investment decisions: It is one of several factors that can be beneficial in making informed investment choices.
Limitations of tracking error
Despite its usefulness, tracking error has some limitations:
- Past performance: It is based on historical data and may not accurately indicate future performance.
- Short-term fluctuations: It may not capture temporary deviations from the benchmark.
- Index changes: Adjustments in the benchmark’s composition or methodology can affect tracking error.
- Expense ratio changes: Changes in a fund’s expense ratio will directly impact its tracking error.
Read Also: Tips to choose the right index fund for your portfolio
What do high and low tracking errors indicate?
A low tracking error indicates that the index fund has been able to closely mirror the movements of its underlying index. This may suggest that the fund’s portfolio construction, rebalancing process, and cost management have helped minimise deviations from the benchmark. For investors seeking passive exposure to an index, a lower tracking error may indicate more efficient index replication.
A high tracking error indicates larger variations between the fund’s returns and the benchmark’s returns. It suggests that the fund has not tracked the index as closely over a given period.
Comparing ex-post and ex-ante tracking errors
While both relate to deviations from the benchmark index, they differ in terms of the time period they evaluate and the purpose they serve.
Ex-post tracking error is a historical measure. It calculates the actual variation between the returns of an index fund and its benchmark over a past period. This metric helps investors understand how closely the fund has tracked the index based on realised performance data.
Ex-ante tracking error is a forward-looking estimate. It attempts to predict the potential variation between the fund’s future returns and those of the benchmark. This estimate is based on factors such as portfolio composition, expected transaction costs, cash holdings, rebalancing requirements, and market conditions.
Tracking error vs tracking difference
Tracking error and tracking difference are both used to understand how closely a fund follows its benchmark, but they measure different aspects of performance.
| Parameter | Tracking error | Tracking difference |
| Meaning | Measures how much a fund’s returns vary from its benchmark returns over time. | Measures the difference between a fund’s return and its benchmark return over a specific period. |
| What it shows | How consistently the fund follows the benchmark. | Whether the fund has underperformed or outperformed the benchmark. |
| Focus | Volatility of the return difference. | Average return gap between the fund and the benchmark. |
| Calculation | Standard deviation of the difference between fund returns and benchmark returns. | Fund return minus benchmark return. |
| Used for | Understanding how closely an index fund or ETF tracks its benchmark. | Understanding the actual return gap between the fund and its benchmark. |
| Interpretation | Lower tracking error means the fund is following the benchmark more closely. | A lower tracking difference means the fund’s return is closer to the benchmark return. |
| Example | If the fund’s return gap from the benchmark changes sharply each month, tracking error may be high. | If a fund gives 11% and the benchmark gives 12%, the tracking difference is -1%. |
Conclusion
Data on tracking error helps you assess how your fund is performing relative to its benchmark. For an index fund or a passively managed fund, too much variance, especially over multiple periods, can be indicative of high volatility. It is therefore important for investors to look at tracking error data when evaluating their investments.
FAQs
What does a low tracking error indicate?
A low tracking error means the fund closely follows the benchmark index’s returns. This is common in index funds and ETFs designed to replicate index performance.
What are some of the sources of tracking errors?
Factors include fund management expenses, cash holdings, portfolio sampling differences, and delays in adjusting holdings. Regulatory restrictions on certain stocks can also cause deviations.
How does tracking error affect index funds vs active funds?
Tracking error affects index funds and active funds differently. In index funds, it indicates how closely the fund has replicated its benchmark—lower tracking error is generally considered suitable. In active funds, tracking error reflects how much the fund’s returns deviate from the benchmark due to active investment decisions. A higher tracking error in an active fund is usually expected and may be suitable if the fund manager is intentionally taking differentiated positions to generate alpha (excess returns).
Can tracking error be negative?
Tracking error cannot be negative because it is a statistical measure based on standard deviation. It reflects variability, not direction. While tracking difference may be positive or negative, tracking error remains a non-negative value.
How does tracking error relate to fund expense ratio?
The expense ratio is an important contributor to tracking difference because it reduces the fund’s returns relative to the index, leading to a consistent return gap. While the expense ratio itself does not typically increase tracking error, other costs—such as transaction costs, impact costs during rebalancing, and operational factors—may create variability in returns and therefore contribute to tracking error.
What does a high tracking error mean for an investor?
A high tracking error has different implications depending on the type of fund. In an index fund, a high tracking error suggests the fund is struggling to closely replicate its benchmark. This may happen due to factors such as higher cash holdings, sampling instead of full replication, securities lending practices, transaction costs, or delays in executing index rebalancing. For an active fund, a high tracking error simply indicates that the manager is taking considerable active positions relative to the benchmark—reflecting higher active risk aimed at potentially delivering differentiated performance.
How often is tracking error calculated and reported?
All ETFs and index funds must disclose tracking error based on past one-year rolling data on the websites of respective AMCs and AMFI.
