For decades, the defined contribution industry has focused on the performance of individual funds at the expense of other plan metrics. In this paper, we analyze a series of variables - fund selection, asset allocation, portfolio rebalancing, and increasing deferral rates - to determine which factors may have the greatest potential impact on an individual's portfolio. Our analysis suggests that putting fund performance front and center in terms of the plan sponsor's priorities is an error with far-reaching implications. That is not to say that fund performance does not matter, but our analysis suggests it is a much less powerful variable compared with asset allocation and, most of all, higher deferral rates.
What Matters Most?
In this study, we begin with the question "What matters most?" - asking it on behalf of DC plan sponsors and participants who wish to secure better retirement savings outcomes. Since the advent of DC plans, the lion's share of attention has focused on fund performance. Indeed, on an annual and even more frequent basis, plan sponsors have long sought to identify and stock their DC plans with the best-equipped investment vehicles for growing participant wealth. Furthermore, in accordance with their role as fiduciaries, plan sponsors have spent significant time and resources educating their participants about the value of diversification, portfolio rebalancing, and saving more. But which of these factors matters most? Or do they rate about evenly in terms of their importance? What is the best use of the plan sponsor's time and energy?
In pursuit of answers to these questions, this study quantifies the hypothetical impact of individual fund performance using several fund selection methodologies. It then moves to an assessment of asset allocation, rebalancing, and deferral rate increases. The end goal is to quantify the practical impact of specific tactics that may help steer plan sponsors and advisors away from an excessive, fund-centric focus. As we will show, there may be better ways to spend your time.
The Base Case
We begin our analysis by formulating a base-case investment scenario for an individual's portfolio. We assume the individual was 28 years old in 1982, earned an income of $25,000 per year, and received a 3% annual cost-of-living increase. Because it falls close to the inception of defined contribution plans in the United States, 1982 is a good year in which to start our analysis. In addition, the individual's $25,000 annual salary is in line with Bureau of Labor Statistics data reporting average salaries for a variety of professional classes at the time. The 401(k) plan available to this individual offers a match of $0.50 on the dollar up to 6%. Furthermore, this person was invested in a conservative asset allocation across six asset classes. Also, as an important controlling factor in our study, for each asset class we assume contributions are invested in a 4th-quartile fund - a fund ranking among the bottom 25% of its Lipper peer group - based on three-year performance data. We also assume that the individual deferred 3% of gross salary into the plan, that there is no rebalancing of account assets, and that no asset allocation changes are made over time. Twenty-nine years later, the individual was 57 years old, earned an income of $57,198 per year, and had a 401(k) balance of $136,400.
1. The First Driver: Fund Selection
From our base case (4th quartile fund selection), we will now investigate drivers of retirement wealth accumulation by considering the impact of having a different fund lineup. Rather than the 4th-quartile portfolio, we will look at four other fund selection scenarios, three of which might generally be regarded as realistic strategies, with the fourth being unrealistically "perfect."1
First Quartile. The first hypothetical scenario is a buy-and-hold strategy in which only 1st-quartile funds (at or near the 25th percentile) were held for the 29-year investing period. That is, we substitute 1st-quartile funds, based on their three-year ranking as of December 31, 1982, instead of using 4th-quartile funds, and assume the individual holds these funds, as in the base case, throughout the 29-year time frame.
Three-Year Rotation. In the second hypothetical scenario, we select an initial lineup of 1st-quartile funds, again based on three-year peer-relative performance, but this time, to the extent that funds have fallen out of the 1st quartile after three years, we replace them with new 1st-quartile funds (funds at or near the 25th percentile). This process repeats itself every three years. This is a typical practice employed by many plan sponsors as they seek to comply with their Investment Policy Statement.
Index Funds. In the third hypothetical scenario, we assume that rather than focus on actively managed funds, the plan sponsor seeks to reduce cost by choosing index funds. These investments are assumed to be held for the entire period under analysis.
Crystal Ball. In this hypothetical scenario, we assume that the plan sponsor would have used a crystal ball to predict funds in the 1st quartile for the next three-year period and accordingly put these in place ahead of time on a rolling three-year basis. If it were possible, this strategy will always give the individual marginally better investment returns.
Interestingly, regardless of strategy, fund selection generated roughly the same amount of wealth (Figure 1). The crystal ball strategy improved the base case by roughly $30,000. Having perfect foresight and being able to predict future 1st-quartile funds would have improved the individual's outcome by a 22% cumulative difference above the $136,400 obtained in the basecase strategy.
What is surprising is that in the study the best strategy that one could implement was the base case itself, where terminal wealth was between roughly $5,000 and $10,000 ahead of the indexing, three-year rotation, and 1st-quartile strategies. This illustration offers an important caution for those who think that a fund's track record is an indication of its future success. It would sound prudent to put a 1st-quartile strategy in place, or to monitor and manage the lineup so it always made "good" funds available to participants. But when we map out the alternatives, the differences - even over a long time frame - are relatively small, and importantly, changing a plan's underlying funds for justifiable seeming reasons may in fact detract from performance.
2. The Second Driver: Asset Allocation
Turning from investment selection, we look next at the potential impact of adjusting the portfolio's asset allocation. After all, if the base case relies on a conservative portfolio allocation, perhaps a larger allocation to equities and a smaller allocation to fixed-income components could have a meaningful impact on portfolio results, particularly over a time frame of 29 years.
Leaving the 4th-quartile base portfolio in place, we dial up its risk/return profile, taking the asset mix from a conservative model (30% equity) to a balanced (60% equity) as well as to a growth (80% equity) model. Figure 2 breaks down each asset allocation into equity and fixed-income subcategories that map onto the Lipper classifications used in our study.
When we calculate returns for these hypothetical portfolios over our 29-year time frame, it appears that results would be moderately better in both the balanced and growth portfolio models, which returned approximately $14,000 and $23,000 more, respectively, than the base-case portfolio (Figure 3).