The term referring to a fund’s disparity from its benchmark is widely known — but not necessarily well understood
In an industry like financial services, a lot of time can be saved by referring to commonly understood jargon or terms of the trade. Portfolio managers and advisors, for example, might refer to the phrase “tracking error” when discussing ETF performance.
But as a blog post published by State Street Global Advisors explains, it might be worthwhile asking exactly what someone means when using the term. “The term ‘tracking error’ gets thrown around a lot in the industry, but it can refer to two different measurements,” wrote James Ross, chairman of the Global SPDR Business.
One measurement, the tracking return difference, looks at the difference between an ETF’s benchmark and its net asset value (NAV) return; the smaller its absolute value, the better. Determined over a particular period, the tracking return difference can be negative or positive, though it’s more typically negative due to the impact that a fund’s expense ratio can have on its returns.
The other measure, tracking return volatility, measures the variability of an ETF’s excess return. By taking the annualized standard deviation of the difference in the ETF NAV and index returns, one can get a sense of how consistent a fund’s performance is; the smaller the figure, the more consistent the fund performance. “This measure is more commonly used … for active management as a way to examine how much risk an active manager is taking versus an index,” Ross said.
While large tracking error could be a red flag for a passive ETF — it could be symptomatic of excessive trading costs or fund-management issues — it’s a natural part of investing. Aside from fees, funds have to deal with cash drag: any cash positions it holds will not benefit from market advances. Passive ETFs tend to have low cash weightings in their portfolios, but that can shift because of dividend payments.
The replication, weighting, and rebalancing methodology of a passive ETF could also have an impact on tracking error. Predictably, a full-replication ETF — one that holds all its securities at the same weights as its underlying index — typically have a lower tracking error than an optimized ETF that closely matches the index’s characteristics without mirroring its underlying securities exactly. Strategies that hold less liquid securities like high-yield bonds or emerging-market debt can also have higher tracking error as a result of generally higher transaction costs.
“Assessing tracking error requires an in-depth analysis, especially when the error appears to be large,” Ross said, emphasizing the need for multiple time periods and data points. Expanding an analysis beyond a single timeframe to instead focus on rolling periods could reveal changes or aberrations in a fund’s tracking error.
He also stressed that those gauging an ETF’s performance should go beyond looking at its expense ratio, as other variables can add to the total cost of ETF ownership. “Different approaches to managing an ETF dictate how closely a fund may track its index—and how well a fund may suit your particular portfolio,” he said.