Digging deeper into target-date fund dispersion

An analysis uses modern models to account for differences in risk and return performance within the same target date

Digging deeper into target-date fund dispersion

While target-date funds are promoted as a simple “set-it-and-forget-it” solution, finance experts know that they’re actually more complicated than investors realize. While they are designed based on assumptions of the typical investor’s needs, they can fail to account for non-typical investors.

Another problem, as noted in a new blog post published by MSCI, stems from the differences in return and risk profile that arise even among funds with the same target date. While features such as their glidepath philosophy and decisions on whether they’ll pursue a “to vs. through” retirement design can account for some of the difference, those explanations only go so far.

“Our research shows there may be more to the story when it comes to understanding TDF portfolio construction and performance,” wrote Anil Rao, executive director of Equity Solutions Research at MSCI.

He illustrated with an examination of the returns of funds aimed at three retirement dates — 2020, 2030, and 2040 — with around 30 funds falling under each cohort from 2016 to 2019. For each target, the average equity allocation gets progressively aggressive at about 50%, 70%, and 80%, respectively. Traditional balanced funds were also viewed for comparison.

“Given the upward-trending equity market of the last three years, it’s perhaps unsurprising that the 2040 funds, on average, delivered the highest returns,” Rao said.

He reported that the TDFs in the sample displayed a tighter range of outcomes compared to balanced funds, whose range of risk and return overlapped with those observed for each of the three target dates. But even within the same target-date cohort and within the relatively short three-year period of the analysis, researchers found wide dispersion in risk (approximately 2%5-5% dispersion) and return (approximately 3%-5% dispersion).

Focusing on the 2030 cohort, they compared funds’ performance with that of a blended benchmark (70% the MSCI ACWI IMI equity index and 30% the Bloomberg Global Aggregate Bond Index) that represented the average allocation of the sample of funds. While they reportedly kept pace with the benchmark on average, there was wide disparity between the bottom and top performers, ranging from -8% to 4% relative return as of the end of March 2019.

Three funds were then taken from the 2030 cohort — one underperforming, one average, and one outperforming — and compared with the 70.30 blended benchmark in terms of their holdings and underlying risk exposures. Overall, each fund displayed similar overall levels of historical and forward-looking active risk (approximately 200 basis points). They also had an underweight to emerging-market equities, with muted tilts toward factors such as momentum, size, value, and volatility.

But a look at their largest sources of active risk revealed stark differences. The outperforming fund had a massive overweight to the US equity market, while the underperforming fund’s risk came primarily from an underweight to equities and, to a lesser but still-meaningful extent, a bias toward larger stocks. The average fund, meanwhile, derived the most risk from sensitivity to US interest rates, despite having a slight underweight to equities.

“It may be that, other than its exposure to riskier, more volatile stocks, its equity allocations were the most similar of the three funds to the benchmark’s equity allocations,” Rao hypothesized.


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