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When tasked with providing a birthday cake for a party, you typically can do one of two things – either buy a pre-made birthday cake, or buy all the individual ingredients and make the cake yourself. I’ll be the first to admit, I run straight to the bakery section of my local grocer to purchase the already constructed cake, as they are the professionals, and I am far from it.

 

This analogy is similar to investing in a self-directed 401(k) plan. Participants of employer sponsored 401(k) plans typically have a similar decision to make. Either they can select their investments from the myriad of mutual fund offerings and determine the appropriate mix, or they can invest 100% into a target-date fund based on their retirement date.

 

Based on this analogy, one can see why target-date funds have grown in popularity, particularly in 401(k) plans. Target-date funds make life easier for the individual plan participants, which is most important, however, they can cause headaches for the fiduciary who is tasked with analyzing the different offerings.

 

In the below analysis, we show how fiduciaries can use returns based style analysis (RBSA) to determine the factors that contribute to the under/outperformance of target-date funds.

 

In the example below, we selected target-date funds that range in retirement dates (2020, 2030, and 2040), from two different fund families (ABC Investments and XYZ Funds). Figure 1 displays the annualized returns of the individual funds for the two different fund families.  As you can see, the ABC Investment funds outperform across the board.

  

 Figure 1

 

We could stop here, but a complete analysis doesn’t end at returns. By definition, target-date funds invest in a wide array of different investments, at different weights. A comprehensive analysis should include an understanding of what factors contributed to ABC fund’s outperformance and XYZ fund’s underperformance.

 

Managers of target-date funds are allowed flexibility over their asset allocation decisions, as their portfolio allocations may differ within the same retirement target-date category. As one can expect, individual mangers may have varying opinions on what an optimal allocation is for an investor retiring in 2040. These allocations are very important, as over 90% of a portfolio’s variation in returns are attributed to asset allocation.[1] The underlying investments of each fund also drive performance for the individual target-date funds. It is important to understand whether the over/underperformance is due to allocation decisions or the selection of the underlying investments.

 

In this analysis, we used the below five asset classes and the representative index to conduct the RBSA analysis.

 

ASSET CLASS

INDEX

U.S. Stocks

Russell 3000

Foreign Stocks

MSCI World Ex. U.S.

U.S. Fixed Income

Bloomberg Barclays U.S. Aggregate

Foreign Fixed Income

Citigroup Non-USD WorldBIG

Cash

Citigroup 3-Month T-bills

 

Due to the managers’ flexible asset allocation mandates, locating an appropriate benchmark when comparing funds with similar objectives, but different allocations, can be troublesome. Not all is lost however, as RBSA provides fiduciaries the perfect tool to solve this problem.

 

We can use RBSA to create style benchmarks, which are unique combinations of the five indexes listed above that does the best job of mimicking the performance of the individual funds. Each of the eight funds has its own unique style benchmark based on the fund’s return behavior. These unique, best-fit, style benchmarks provide fiduciaries the ability to identify the asset allocation decisions of each fund.

 

As you can see in figure 2, there are some fundamental differences in the allocations between the two fund families. Worth noting, XYZ Funds generally overweight U.S. equities, while ABC Investments overweight foreign equities across the board. Interestingly, U.S equities have outperformed foreign equities by a wide margin over the past ten years, so one would expect the XYZ funds to outperform due to their overweight in the best performing asset class over the past ten years. However, that is not the case, as the ABC funds outperformed while underweighting the best performing asset class. Generally speaking, the asset allocation decisions had less impact on the outperformance for ABC funds.

 

Figure 2 – Asset Allocation June 2007 – June 2017 (36-Month Moving Windows, Computed Monthly)

 

Next, we can use the unique style benchmarks to determine what effect the underlying investments had on performance. Using the style benchmarks allow us to neutralize the effects of the asset allocation decisions when comparing different performance statistics versus the best-fit style benchmark. Figure 3 shows the impact that the underlying investments had on the overall performance. It is easy to see that ABC funds outperformance is due to the selection of the underlying investments. Each ABC fund has superior alpha, excess return, and information ratio. Figure 3 also tells us that an investor would be better off investing in a set of ETFs, or passively managed investments that follow the asset allocation detailed in figure 2 for XYZ funds. Based on this analysis, the asset allocation decisions contributed positively to the performance, while the investments selected had a negative impact on XYZ funds.

 

When conducting this analysis, it is imperative that you have a best-fit benchmark, so one can eliminate allocation biases and focus on the performance. As you can see, the r-squared for all funds is very high, telling us that the style benchmarks provide the best-fit benchmark for each product.

 

Figure 3

 

Target-date funds offer great advantages for investors looking for a ready-made solution, however, these investments provide difficulties for fiduciaries. RBSA allows professionals the ability to eliminate these hardships and accurately determine what contributed to the overall fund performance, while conducting an apples-to-apples comparison of the different options.

 

[1] “Determinants of Portfolio Performance,” Gary P. Brinson, L. Randolph Hood, and Gilbert P. Beebower,

                Financial Analysts Journal, July/August 1986.

 

Ryan Nauman is a VP, Product and Market Strategist at Informa Financial Intelligence.

 

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