Markov Processes International

Shaking The Nest Egg: Using Scenario Analysis to Choose The Right Target-Date Fund

This is the fourth installment in our series on risk, in which our research team leverages new investment risk analytics in Stylus Pro to demonstrate how historical and forward-looking stress tests can provide deeper insight into fund performance across various market regimes and hypothetical scenarios.

In this post, we take a more granular look at a group of 38 funds within the 2020 target-date vintage, which is the vintage intended for investors planning to retire in or around 2020. Near-dated target-date funds (TDFs) may have widely varying allocations to growth assets (primarily stocks).

2020 TDFs average approximately 50% in growth assets and 50% in bonds, or preservation assets, according to a 2017 Morningstar report1 and corroborated by returns-based style analysis.2 Some TDFs continue to reduce exposure to growth assets past the retirement date (through funds), while others have a landing point at the fund retirement date (to funds). Generally, we would expect the former to be more aggressive with higher exposure to growth assets. These and other allocation differences allow funds of the same vintage to match different investor profiles, which may also have different tolerance thresholds for different shocks.

In the below chart, we look at a universe of 38 unique TDFs dated 2020, using a single share class from each fund and estimate their sensitivity to six individual shocks,3 none of which has occurred on a monthly basis4 within the past five years.

We also select three TDFs within this vintage to compare against the entire peer group (indicated in gray) in order to more explicitly illustrate varying sensitivities across a group of funds that share several common characteristics. The three selected TDFs have similar five-year standard deviations (approximately 5.2%) and similar returns-based style analysis estimates of growth asset allocations (46%-48%).

While we don’t see anything that hints at the extreme sensitivity of some near-dated funds in 2008, we do see a broad range of sensitivities as indicated by the peer distribution spanning the 5th to 95th percentiles.

From this analysis, we can observe the following:

These differences (given that we took funds with similar growth asset estimates using returns-based style analysis) are likely to be primarily due to sub-strategy allocations.

Using scenario analysis, we can infer the following differences in the sub-strategy allocations:

If we have a strong opinion on what a future shock may be, then we can evaluate a broad range of funds or portfolios against that specific scenario within seconds. Without the strength of conviction, scenario analysis can provide insight into fund sensitivity against an array of scenarios. This multiple scenario approach to fund analysis can help to ensure that no fund exceeds a threshold loss estimate in any scenario.


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