Is the factor tilt in a portfolio too much, too little, or just right? Tracking error can help to answer that question.
In the pursuit of enhanced risk-adjusted returns, investors with strong convictions are often drawn to . Factor investors often tilt portfolios toward a particular factor like value, low volatility, or dividend yield in hopes of generating long-term investment returns that outperform benchmarks. Factor investors also construct multi-factor portfolios, blending factors to moderate risk and drive returns.
While it may seem counterintuitive—especially because investors are not big fans of errors—a factor portfolio’s can be a useful tool for investors who want to ensure they’re not taking on too much risk or unintended exposure in an attempt to generate benchmark-beating returns.
What is factor investing?
Before jumping into tracking error, let’s look at how factor investing works. Factor investing is based on the premise that a set of common factors can explain the differences in stock returns. Popular factors include the ones mentioned above—value, low volatility, and —as well as quality and momentum.
Relative to a cap-weighted portfolio, factor-based portfolios emphasize factors to enhance returns. For example:
Factor investing and tracking error
All portfolios, including factor portfolios, behave slightly differently from their benchmarks on a day-to-day, month-to-month, and year-to-year basis. There’s always a difference in a portfolio’s performance relative to its benchmark, and tracking error .
In general, factor-based investing seeks outperformance by maintaining a systematic bias toward an intended factor, using a universe of stocks as the starting point for the portfolio. This bias means these portfolios are built to diverge meaningfully from an index. Research estimates that the predicted tracking error of a factor strategy ranges between 3% and 6%. Factor investors have shown a willingness to accept a higher tracking error—or higher risk—in pursuit of higher excess return potential.
While tracking error may help factor investors assess how much a portfolio may deviate from a benchmark index, it’s also a useful measure for keeping a portfolio aligned with an investor’s goals. Here are three ways how:
- 1. It measures the magnitude of your tilt. Factor investors typically tilt portfolios toward factors they believe will outperform over time. Tracking error comes in handy when it comes to determining how far a factor tilt should go. For instance, let’s say the investor has constructed a momentum-tilted portfolio that has a 3% tracking error compared with its benchmark. This tracking error means the portfolio has a 68% chance of delivering a return within 3% of the index and therefore a 32% chance of exceeding 3% above or below the index. An investor who is bullish on momentum may feel this is an appropriate level of risk to take in the search for returns and the factor tilt does not need to be adjusted. On the other hand, let’s consider an investor who’s constructed a momentum-tilted portfolio, and this time it has a 5% tracking error. The portfolio now has the same probabilities as above but with materially wider outcomes. This performance deviation may feel too risky, and the factor tilt can be dialed down.
- 2. It helps set realistic alpha expectations. Tracking error describes the size of the difference in relative return, not whether the return was positive or negative. That means the greater the tracking error, the greater the possibility for very positive—or very negative—excess return. Tracking error can provide an investor with a clearer sense of how much risk is built into their portfolio, allowing them to assess whether they’re comfortable with the degree of underperformance they may experience in the hunt for alpha. On the flip side, tracking error can also help to keep an investor’s expectations in check by indicating the likely upper bound of excess return for their portfolio.
- 3. It can control for unintended exposure. It isn’t reasonable for a portfolio’s target factor to produce 100% of its tracking error. Why? Because it’s nearly impossible to implement a factor exposure without introducing a sector, security, or country exposure as well. For instance, a factor portfolio with a value tilt could also increase exposure to the financial sector because financial stocks tend to exhibit low price-to-book ratios. Factor portfolios need to control for these unintended exposures, however, so the desired factor is the primary driver of tracking error. Constraints can be implemented to mitigate the effects of unintended concentrations and ensure that more of the tracking error results from tilts toward the target factors, not unintended exposures.
The bottom line
Introducing systematic bias toward factors in a portfolio can deliver an attractive risk-return profile over time. While this bias produces tracking error, this error is a helpful measure investors can use to fine-tune their factor portfolio and ensure it’s aligned with their risk tolerance and long-term investment objectives.