This article is part of a regular series of thought leadership pieces from some of the more influential ETF strategists in the money management industry. Today's article is by Corey Hoffstein, co-founder and chief investment strategist of Boston-based Newfound Research LLC.
In certain circles, minimal tracking error is a good thing. Tracking error is a mathematical measure that captures the magnitude of return deviations between a portfolio and its benchmark. Mutual funds and ETFs that are tracking an index are evaluated on their ability to minimize tracking error to that index.
Tracking error is calculated as the standard deviation of active returns—which, again, are the difference between portfolio returns and benchmark returns.
Let’s consider the following example:
We can see that in some cases, the portfolio had a positive active return and in other cases, a negative one. For indexed funds, we want the long-term average and standard deviation to be as close to zero as possible. For tactical strategies, however, we want the expected active return to be positive. Very positive.
Positive Tracking Error
As we are keen to say in the risk management side of finance, past performance is not indicative of future results. Theoretically, a positive expected active return has to come from some deviation, or risk taking, away from the benchmark portfolio allocations.
For example, if the active return column read 2 basis points every month, the expected active return would be 2 basis points, and the standard deviation of active returns would be zero basis points, acknowledging the consistency of this performance.
But for the paranoid risk manager, there is nothing that says a consistent +2 basis points couldn’t become a consistent -2 basis points very quickly if the market turned against the manager.
Therefore, to take a more paranoid view of risk, we can assume a zero-basis-point expected active return.