Assessing whether a target-date fund (TDF) series is performing as expected can be a difficult undertaking. Each TDF series features multiple vintages, each with its own asset allocation. And each TDF provider takes a different approach to glide-path construction, sub-asset allocation, and benchmark implementation and rebalancing. Further, the investment life cycle of a TDF is measured not in months or years but decades. This means that there is simply no single metric that can definitively answer the question "Is my TDF doing its job?"
To adequately gauge TDF success and compare providers, investors, plan sponsors, and consultants need to assess a mosaic of different metrics to see the full story. Of all the metrics investors consider to determine whether a TDF is doing its job, the two most important are risk-adjusted returns and retirement readiness outcomes. These two metrics most closely align with the goal of a TDF, which is to accumulate enough wealth to generate sustainable income in retirement.
In light of the recent market volatility experienced in the first half of 2020, two metrics that usually play a lesser role in TDF evaluation have gained considerable attention: excess return and tracking error. Excess return is simply the difference between the performance of a fund and its benchmark, while tracking error is the standard deviation of this difference. While these two metrics are among the most practical in evaluating the effectiveness of index funds, they do very little to tell you whether your TDF is performing as expected when not combined with additional supporting data.
Still, we appreciate that these measures can be brought into the broader mosaic of TDF assessment and, therefore, warrant a deeper dive. Importantly, to use these metrics appropriately, we believe investors need to understand how a TDF provider approaches benchmark implementation and rebalancing, as there are considerable differences across providers that result in trade-offs that can impact investor outcomes.
Index-based TDFs are not index funds
While index-based TDFs are constructed with index funds, they themselves are not index funds and thus are not managed like index funds. An institutional-caliber asset manager can construct an S&P 500 Index fund so that the fund's holdings come close to precisely replicating the index. Absent large cash flows or structural changes to the benchmark, most S&P 500 Index funds require only a modest amount of trading to track their benchmark regardless of the volatility of the market. Why? Because the S&P 500 Index constituents are market-cap-weighted. So, if one stock significantly underperforms the market, that underperforming stock will automatically become proportionately less in the index and the fund that tracks the index, all else being held equal. No transaction costs required.
Most index-based TDFs, on the other hand, maintain strategic allocations to varying asset classes that gradually adjust over time as they roll down their glide path to a landing point. Therefore, if one asset class (e.g., stocks) significantly underperforms another (e.g., bonds), and cash flows are not significant enough to rebalance back to desired weights, then the manager needs to sell the outperforming asset class (bonds) and purchase the underperforming asset class (stocks) to realign the portfolio back to target weights. Large market swings can result in more substantial trading between asset classes and typically coincide with increased transaction costs. To keep trading costs reasonable in volatile markets, TDF providers have higher tolerances for excess return and tracking error than would be allowed for most index funds.
TDF benchmark rebalancing differences and trade-offs
There are important differences between TDFs from various providers. Glide-path and sub-asset allocation differences are the most obvious. Less discussed are differences in benchmark construction and rebalancing methodologies.
There is no standard or consistent methodology across the TDF industry. Each TDF manager defines the benchmark and the rebalance policy for their funds and the associated benchmarks. For example, some TDF providers rebalance benchmarks daily, while others do so monthly or quarterly. Some TDF providers allow fund allocations to drift from target allocations within the rebalancing period, while others rebalance if the funds drift too far from target allocations, staying within defined threshold bands relative to strategic glide-path allocations.
These variations make an apples-to-apples comparison of tracking error and excess return results difficult across TDF providers, as each approach comes with trade-offs, as shown in Figure 1.
Figure 1 Trade-offs of different benchmark rebalancing frequencies.
Source: Vanguard Risk Management Group research conducted from May 2020 through September 2020.
For example, a TDF can "track" its benchmark tightly simply by aligning the rebalance frequency of the fund and the benchmark. If the rebalance frequencies are set at monthly, both the fund and the benchmark asset allocations will float between rebalances and then be brought back to the target allocation at the end of the month. This may make it seem like the TDF did a better job of tracking the benchmark but risks substantial variations from the target strategic asset allocation between rebalances, which in turn can produce returns that vary substantially from those intended by the glide-path design.
To bring this concept to life, let's examine the asset allocation differences between a benchmark that rebalances its weights back to target on a daily basis versus the same benchmark that rebalances on a monthly basis.
Consider the volatile March 2020 market environment to illustrate how these differences can play out, as illustrated in Figure 2. The daily rebalance benchmark started the month at a 50% stock and 50% bond allocation and rebalanced back to a 50% stock and 50% bond allocation each and every day for the entire month.
Figure 2 The asset allocation impact of different rebalance frequencies
A benchmark that is rebalanced monthly risks deviating significantly from the investor's expected glide path, as you can see in the left side of Figure 2. We rebalance our benchmark daily because we believe it provides the best representation of the glide path each day of the month, as you can see on the right side of Figure 2. We then rebalance the portfolio to the benchmark in a way that strikes the optimal balance between transaction costs and adherence to the glide path.
This chart is for illustrative purposes only and is not indicative of any specific investment.
Bond returns are represented by the Bloomberg Barclays US Aggregate Float Adjusted Index (70% allocation) and the Bloomberg Barclays Global Aggregate ex-USD Float-Adjusted RIC Capped USD Hedged Index (30%).
Stock returns are represented by the performance of the CRSP US Total Market Index(60% allocation) and the FTSE Global All Cap ex US Index (40%).
Source: Vanguard.
The monthly rebalance index started at a 50% stock and 50% bond allocation, but eventually reached a 43% stock and 57% bond allocation on March 23 as stocks significantly underperformed bonds. Investors putting money to work on March 23, 2020, may have thought they were getting a 50% stock and 50% bond allocation mix but instead would have a significantly different experience.
At Vanguard, we rebalance our TDF benchmarks daily as we believe this provides the best representation of the glide path each day of the month, whereas a benchmark that is rebalanced on a monthly or quarterly basis can meaningfully drift from the expected asset allocation experience. We believe that this is especially important for TDFs as they receive contributions from millions of investors each trading day.
Striking the appropriate balance—Vanguard's approach to TDF rebalancing
Of course, no one can invest in a frictionless benchmark. All TDFs must incur some sort of transaction costs to invest hard-earned investor contributions and to rebalance portfolios back to target allocations. So while the daily rebalanced benchmark keeps allocations more aligned to target allocations, it comes with a higher frequency of transactions to do so.
The primary objective of the Vanguard Target Retirement Fund rebalance policy is to strike the optimal balance between minimizing transaction costs and closely maintaining the target strategic asset allocation, or glide path, on a daily basis. The objective of our policy is not to minimize tracking error to an uninvestable benchmark. Seeking the appropriate rebalancing method is an exercise in identifying the rebalancing "trigger point" beyond which the value of rebalancing (maintaining the target strategic asset allocation) outweighs its cost (transaction costs).
Within this context, there exist two primary rebalance methods used across the TDF industry. The first method is calendar-based, where portfolios are rebalanced at predetermined time intervals, such as monthly or quarterly. The second method is weight-threshold-based, where portfolios are rebalanced if the portfolio's asset allocation has drifted from its target strategic asset allocation by a predetermined minimum threshold.
At Vanguard, we take a weight-threshold-based approach to TDF rebalancing. This is because performance data indicates that a weight-threshold-based rebalance approach generally produces better results than a calendar-based approach, striking the appropriate balance between minimizing transaction costs and maintaining the target strategic asset allocation, as shown in Figure 3.
Figure 3 TDF rebalance methods: Transaction costs vs. tracking error to target asset allocation
Past performance is not an indication of future performance.
Source: Vanguard. As of 9/30/2020.
*Based on a hypothetical 60% global equity and 40% global fixed income portfolio using the actual historical returns of the underlying indexes. The simulation used a daily return series under each rebalancing approach, assuming no daily cash flow. Equities allocation based on performance of Russell 3000 Index (36%) and MSCI All-Country World ex USA Index (24%). Bond allocation based on Bloomberg Barclays U.S. Aggregate Index (28%) and Bloomberg Barclays Global Aggregate ex-USD (12%).
In practice, we first use daily cash flows to maintain portfolio level allocations. If daily cash flows are insufficient to bring the portfolios within the threshold band of the target asset allocation, we then buy and sell securities to realign the funds' asset allocation back with the target.
This policy provides a consistent framework for rebalancing, but it's important to note that management of TDFs requires a certain degree of portfolio manager judgment, particularly during abnormal market environments. Implementation should not be blindly systematic. As Figure 3 shows, during periods of market stress, such as 1Q 2020, "widening" threshold bands can be in the long-term best interests of investors. During these periods, portfolio managers use their knowledge of markets and underlying fund liquidity to appropriately weigh rebalancing trade-offs.
Throughout the volatile first quarter, our rebalance policy struck the appropriate balance based on what we aimed to achieve. It kept investors close to their target asset allocation—the Vanguard Target Retirement Funds never deviated by more than 2% from their target weights on a given day–while also ensuring that transaction costs were kept to a minimum.
Investor outcomes over optics
While excess returns and tracking error to a benchmark are among the primary metrics used to effectively evaluate index fund performance, they only tell part of the story when applied to index-based TDFs. We believe it is critical that any evaluation of TDF success starts with long-term risk-adjusted returns and retirement readiness outcomes. If tracking error and excess returns are included in the evaluation, it is important to pair the results with an understanding of the provider's benchmark implementation and rebalance policy, lest you risk a misleading "apples-to-oranges" comparison.
The benchmark implementation and rebalance policies that we have put in place for the Vanguard Target Retirement Funds seek to emphasize investor outcomes—reducing costs, delivering the expected asset allocation experience, and increasing investor wealth—over the optics of tightly tracking an uninvestable benchmark. At Vanguard, everything we do is exclusively focused on providing the best possible investor outcomes—even if it means having more complex conversations along the way—and our Target Retirement Funds are no exception.
Notes:
- Investments in Target Retirement Funds are subject to the risks of their underlying funds. The year in the fund name refers to the approximate year (the target date) when an investor in the fund would retire and leave the workforce. The fund will gradually shift its emphasis from more aggressive investments to more conservative ones based on its target date. An investment in the Target Retirement Fund is not guaranteed at any time, including on or after the target date.
- All investing is subject to risk, including the possible loss of the money you invest.
- The performance of an index is not an exact representation of any particular investment, as you cannot invest directly in an index.