Tracking error is a metric that measures the difference between the performance of a mutual fund and its benchmark index. It’s essential for investors who invest in index funds or exchange-traded funds (ETFs) because these funds are designed to replicate the returns of a specific benchmark. A small tracking error indicates that the fund closely follows its benchmark, while a larger tracking error suggests that the fund deviates more from the index.
How to Measure Tracking Error?
Tracking error is calculated as the standard deviation of the difference in the returns of a mutual fund and its benchmark. The formula for calculating tracking error is:
Where:
- RfR_fRf is the return of the mutual fund,
- RbR_bRb is the return of the benchmark,
- nnn is the number of observations (typically daily, monthly, or quarterly returns).
A lower tracking error means the fund’s performance is more in line with its benchmark, while a higher tracking error indicates greater deviation.
Factors That Affect Tracking Error
Several factors contribute to the tracking error of a mutual fund:
1. Expense Ratios
Mutual funds incur management fees and other operational expenses. These costs can create a drag on performance, leading to a higher tracking error.
2. Cash Holdings
Funds sometimes hold a portion of their assets in cash to manage redemptions. However, cash doesn’t earn the same returns as the index’s securities, which can affect tracking error.
3. Dividend Reinvestment
Timing mismatches in dividend reinvestments can result in deviations from the benchmark, adding to tracking error.
4. Trading Costs and Liquidity
Mutual funds need to trade securities to replicate the index. The transaction costs involved and the liquidity of the securities can contribute to performance deviations.
5. Sampling Strategy
Some funds don’t buy all the securities in an index but rather a representative sample. This may lead to a difference in returns, affecting tracking error.
Example
If a fund aims to track the S&P 500 index and the index returns 8% in a year while the fund returns 7.5%, the deviation is 0.5%. This difference, when tracked over multiple periods, would lead to the calculation of the tracking error.
What is a Good Tracking Error Number?
For index funds, a low tracking error (typically below 1%) is considered good, as it suggests that the fund is closely following its benchmark. For actively managed funds, higher tracking errors are expected due to the active strategies employed by fund managers, but even in such cases, the error shouldn’t be excessively high.
In general:
- Tracking Error < 0.5%: Excellent
- 0.5% < Tracking Error < 1%: Good
- Tracking Error > 1%: Could signal underperformance
Is a High Tracking Error Good or Bad?
A high tracking error is generally undesirable for passively managed index funds since it indicates that the fund isn’t doing a good job of mimicking its benchmark. However, for actively managed funds, a high tracking error could signal that the fund manager is taking risks in an attempt to outperform the benchmark. In such cases, investors may tolerate higher tracking error as long as the fund is delivering superior returns.
In summary:
- For Index Funds: High tracking error is bad.
- For Actively Managed Funds: A high tracking error might indicate the potential for higher returns but also involves more risk.
Conclusion
Tracking error is a crucial metric for assessing how well a mutual fund is replicating its benchmark. While low tracking error is essential for passive funds like index funds and ETFs, higher tracking error may be acceptable or even expected in actively managed funds. Investors should carefully consider tracking error when evaluating mutual funds, as it can reveal insights into the fund’s management and performance consistency.