TDF glide-path essentials: Setting the right starting point

At Vanguard, investor outcomes drive our approach to evaluating and making glide-path changes. Any change that we make represents our belief in that change having an enduring, positive impact on investor outcomes. After rigorous analysis, we have decided to maintain a 90% equity weighting for our glide-path starting point. This article outlines the considerations behind the decision to continue with our current allocation.

The equity weighting across the glide path is one of the most important determinants of TDF outcomes, as it characterizes the trade-off between growth and safety throughout the portfolio s life cycle. While we continuously evaluate the equity weighting as part of our annual glide-path revalidations, we placed additional emphasis on this topic given the strong equity performance in 2023 and 2024.

Much of the industry tends to allocate more heavily toward risky assets, such as equity securities, in the early years of the glide path. Figure 1 illustrates how some of our competitors maintain, or shift to, equity starting points of 95% or higher (relative to our 90% equity starting point). Although it may enhance a TDF's ability to grow wealth over time, a higher equity weighting can also lead to greater-than-necessary risk exposure due to the higher volatility profile that equities have relative to fixed income securities.

While younger investors can potentially better withstand greater market volatility than their older cohorts (and should expect to do so), it does not have a meaningful impact on securing their financial saving goals. Most TDF investors, especially those who are defaulted into an investment plan, skew more conservative given their lack of familiarity with markets and investing. A higher allocation to riskier asset classes and, in turn, more volatility, can be a reasonable decision based on one's risk tolerance. But providers that take this aggressive stance, we believe, can miss the goal of meeting the expected lifetime spending that a glide path will fund. To enable the investor to maintain their lifestyle, we look to replace 79% of an investor's income at age 65 to and through age 95.

The Vanguard Life-Cycle Investing Model (VLCM) provides a robust framework for assessing any potential changes or additions to the glide path. Using the VLCM, our assessment shows that increasing the equity weighting does not provide a meaningful increase in the probability of success, a key metric that estimates the probability of maintaining a positive balance throughout a participant's life.

As previously noted, an increased equity weighting does slightly increase a portfolio's projected median wealth. But while projected increased wealth is a positive, TDFs are not designed as vehicles to maximize wealth. Their purpose is to help participants accumulate sufficient savings by providing a balanced, risk-adjusted path toward retirement. That is why evaluating investor outcomes, through the lens of the VLCM, remains at the center of our approach. Again, we look for changes that exhibit a high CFE benefit (which we define as >10 bps) and a meaningful improvement to the probability of success. As Figure 2 shows, median wealth increases only by about 1% in portfolios with a 95% or 99% starting point, respectively, when compared with portfolios with a 90% equity starting point.

Despite a slight projected increase in total wealth, there is no impact on the probability of success for participants who are invested in portfolios with either a 95% or 99% equity starting point relative to a 90% equity starting point. However, this estimation assumes that participants remain fully invested throughout the course of the TDF and that their contributions remain consistent. It does not account for every investor's risk preference. When you take these factors into consideration, we find it reasonable to maintain the 90% equity starting point.

We appreciate the trust our clients place in us when it comes to allocating their participants' savings. In addition to a rigorous quantitative process, we prioritize participants' sentiments and behaviors to ensure that we meet the needs of a range of investors. Although younger investors can typically endure more risk and be comfortable with portfolio volatility, there is no meaningful increase in the probability of meeting their goal. Let's consider the nuanced cases of younger investors, both those who are unengaged and those who are engaged:

Unengaged investors are those who rarely, if ever, transact in their accounts, a common archetype for direct contribution participants. This, however, should not result in a full risk-on approach unless there is a stated objective driving that decision. It is worth noting that younger investors often face income volatility early in their investment journey as they navigate the job market, variable earnings, and other spending needs, such as student loan repayments. A portfolio with a 90% equity starting point can balance the dual realities of long-term growth needs and short-term income uncertainty.

On the other hand, engaged investors are those who are at risk of making poor decisions if they experience equity corrections early on. For these younger investors, the stability sought by fixed income assets can act as ballast within the portfolio. This ballast will not offset poor equity performance entirely, but it can lessen the blow.

Lastly, there are additional non-participant-based, qualitative aspects to consider, such as plan sponsor and consultant sentiment. Strong absolute returns are always a plus, but we actively balance that objective with the desire to provide a qualified default investment alternative (QDIA) that is well diversified and calibrated to meet participants' financial goals.

We are committed to continually evaluating our glide-path assumptions and measuring the impacts of changing dynamics on a regular basis. This commitment gives us the conviction that our current equity weighting is best suited to meet our clients' needs and is in line with our investment philosophy of creating clear, appropriate investment goals; keeping a balanced and diversified mix of investments; minimizing costs; and maintaining perspective and long-term discipline.

Given their typical use as a QDIA, TDFs require a high bar for change, which is why we prioritize providing actual long-term value for our investors. While increasing the equity weighting would likely boost absolute returns in isolation, it would lead to only a slight improvement in peer-relative results during good years and underperformance during bad ones.

We will continue to monitor and evaluate this assumption and will shift our approach if necessary. However, we believe that a focus on reducing portfolio volatility combined with accessible education, guidance, and advice solutions within a plan will give participants the best chance of staying the course and meeting their retirement saving goals.

Notes:

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All investing is subject to risk, including the possible loss of the money you invest. There is no guarantee that any particular asset allocation or mix of funds will meet your investment objectives or provide you with a given level of income. Diversification does not ensure a profit or protect against a loss. Past performance is no guarantee of future results.

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IMPORTANT: The projections and other information generated by the Vanguard Capital Markets Model® regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. VCMM results will vary with each use and over time.  

The VCMM projections are based on a statistical analysis of historical data. Future returns may behave differently from the historical patterns captured in the VCMM. More important, the VCMM may be underestimating extreme negative scenarios unobserved in the historical period on which the model estimation is based.

The Vanguard Capital Markets Model® is a proprietary financial simulation tool developed and maintained by Vanguard's primary investment research and advice teams. The model forecasts distributions of future returns for a wide array of broad asset classes. Those asset classes include U.S. and international equity markets, several maturities of the U.S. Treasury and corporate fixed income markets, international fixed income markets, U.S. money markets, commodities, and certain alternative investment strategies. The theoretical and empirical foundation for the Vanguard Capital Markets Model is that the returns of various asset classes reflect the compensation investors require for bearing different types of systematic risk (beta). At the core of the model are estimates of the dynamic statistical relationship between risk factors and asset returns, obtained from statistical analysis based on available monthly financial and economic data from as early as 1960. Using a system of estimated equations, the model then applies a Monte Carlo simulation method to project the estimated interrelationships among risk factors and asset classes as well as uncertainty and randomness over time. The model generates a large set of simulated outcomes for each asset class over several time horizons. Forecasts are obtained by computing measures of central tendency in these simulations. Results produced by the tool will vary with each use and over time.

The Vanguard Life-Cycle Investing Model (VLCM) is designed to identify the product design that represents the best investment solution for a theoretical, representative investor who uses the target-date funds to accumulate wealth for retirement. The VLCM generates an optimal custom glide path for a participant population by assessing the trade-offs between the expected (median) wealth accumulation and the uncertainty about that wealth outcome, for thousands of potential glide paths. The VLCM does this by combining two sets of inputs: the asset class return projections from the VCMM and the average characteristics of the participant population. Along with the optimal custom glide path, the VLCM generates a wide range of portfolio metrics such as a distribution of potential wealth accumulation outcomes, risk and return distributions for the asset allocation, and probability of ruin, such as the odds of participants depleting their wealth by age 95.

The VLCM inherits the distributional forecasting framework of the VCMM and applies to it the calculation of wealth outcomes from any given portfolio.

The most impactful drivers of glide-path changes within the VLCM tend to be risk aversion, the presence of a defined benefit plan, retirement age, saving rate, and starting compensation. The VLCM chooses among glide paths by scoring them according to the utility function described and choosing the one with the highest score. The VLCM does not optimize the levels of spending and contribution rates. Rather, the VLCM optimizes the glide path for a given customizable level of spending, growth rate of contributions, and other plan sponsor characteristics.

A full dynamic stochastic life-cycle model, including optimization of a savings strategy and dynamic spending in retirement is beyond the scope of this framework.