Each investor, of course, would have a unique entry and exit point along these timelines, and these specific points will help determine whether their investment under- or outperforms the relevant benchmark.
Even so, VTEB’s returns are distributed more narrowly around those of the relevant benchmark. At the end of any given period, ETF returns clustering tightly around benchmark returns typically results in lower tracking error.
In other words, greater volatility of excess returns translates into more uncertainty around excess returns. And—again—the tighter the tracking error, the more likely it is that you’ll avoid the cost of deviating from the market’s performance, and the easier it is to formulate thoughtful asset allocation.
SCMB only came to market in October 2022; its track record is relatively limited. Still, as these charts show, its excess returns range and its tracking error both exceed those of VTEB and MUB, thus potentially nullifying the benefit of a lower expense ratio.
This case study illustrates how something that seems as mundane as tracking error can play a crucial role in a fund’s risk and return.