Markets and economy

Our time-varying portfolio and a dynamic economy

Our optimal portfolio allocation reflects a remarkable shift in the economy and markets over the last two years.
9 minute read
  •  
July 14, 2022
Markets and economy
Market volatility
Vanguard news
Page
Managing portfolios
Asset mix

As market and economic conditions change dramatically, the chance that an investor won’t meet an important goal—perhaps a level of return or income for a medium-term need—may increase.

Enter Vanguard’s time-varying asset allocation. Our optimal portfolio allocation has changed considerably over the last two years, reflecting a remarkable shift in the economy and markets.

It’s important to understand two things about our time-varying asset allocation approach. It’s not for everyone; it’s intended for investors willing to accept a level of active risk, specifically the risk that our models may not accurately capture economic and market dynamics. And we recommend that investors make us of professional financial advice in relation to time-varying portfolios.

How our time-varying approach works

Typical portfolio construction theory seeks to maximize risk-adjusted returns. “You want a portfolio to get the most return per unit of risk that an investor is willing to take,” said Harshdeep Ahluwalia, a Vanguard senior investment strategist and member of the Vanguard portfolio construction team. “But the definition of risk and return typically changes. What is the expected return of the asset, and what is the volatility, and what is the correlation between them? Let’s form a portfolio with the best trade-off.”

The Vanguard Asset Allocation Model (VAAM) is the vehicle that optimizes the portfolio, mathematically configured to determine that best trade-off. It measures risk not in terms of volatility, as in traditional portfolio construction theory, but rather in terms of distribution of expected returns.

 

Inputs to VAAM come from the Vanguard Capital Markets Model®, which projects the estimated interrelationship among risk factors and asset classes over time. The VCMM produces the 10-year asset-class return outlooks that Vanguard publishes regularly and that are based on the central tendency of the model’s results. (For more on how it works, see the “About the Vanguard Capital Markets Model” section at the end of the article.) VAAM, in assessing risk for its optimal time-varying asset allocations, looks beyond central tendency to the VCMM’s extremes—the expected outcomes at the 5th and 95th percentiles. Greater variation in expected outcomes at those extremes constitutes greater risk.

So for an investor with a 10-year goal, for example, “we’re looking at the end of the 10-year horizon and the dispersion of returns and weighing the trade-offs of different weights to different assets and identifying what provides the best return per unit of dispersion,” Ahluwalia said.

Here’s how our time-varying 60% stock/40% bond portfolio from a U.S. investor’s perspective has changed over the last two years.

Our 60/40 time-varying asset allocation reflects economic, market shifts

IMPORTANT: The projections and other information generated by the VCMM regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. Distribution of return outcomes from VCMM are derived from 10,000 simulations for each modeled asset class. Simulations are as of May 31, 2020; May 31, 2021; and May 31, 2022. Results from the model may vary with each use and over time. For more information, please see the “Notes” section at the end.

Notes: The charts show the optimal allocation to U.S. and international stocks and bonds for a hypothetical investor looking to maximize risk-adjusted returns. Allocations are based on the VCMM forecast at the end of the stated month, which takes into consideration initial market and economic conditions at that point in time and produces a forecast for the subsequent 10 years. Optimization is done using the Vanguard Asset Allocation Model (VAAM), which aims to capture the traditional risk/return trade-offs for beta, factors, and alpha with investors' attitudes toward those risks. The Sharpe ratio is a measure of return above the risk-free rate that adjusts for volatility. A higher Sharpe ratio indicates a higher expected risk-adjusted return. The “benchmark” portfolio is a standard 60/40 stock/bond portfolio with equity home country bias of 60% and bond home country bias of 70%. Home country bias is the percentage of assets in the portfolio that are from a given investor’s region (in this case, U.S. securities for a U.S. investor). U.S. equities are represented by the Dow Jones U.S. Total Stock Market Index (formerly known as the Dow Jones Wilshire 5000) through April 22, 2005; the MSCI US Broad Market Index through June 2, 2013; and the CRSP US Total Market Index thereafter. International equities are represented by the Total International Composite Index through August 31, 2006; the MSCI EAFE + Emerging Markets Index through December 15, 2010; the MSCI ACWI ex USA IMI Index through June 2, 2013; and the FTSE Global All Cap ex US Index thereafter. International bonds are represented by the Bloomberg Global Aggregate Index ex USD, and U.S. bonds are represented by the Bloomberg U.S. Aggregate Bond Index. Portfolio weights may not total 100% because of rounding.

Source: Vanguard calculations, based on data as of May 31, 2020; May 31, 2021; and May 31, 2022.

The chart on the left shows a steady-state, or baseline, portfolio with stock allocations of 60% and bond allocations of 40%. In May 2020, early in the COVID-19 pandemic, stocks had sold off considerably, bringing valuations lower and sending expected 10-year returns higher. “The expected compensation increased for taking more equity risk compared with the steady-state portfolio’s equilibrium risk–return profile,” said Kevin DiCiurcio, who leads the VCMM research team. Such an environment increased the equity allocation to 75%, while allocations to bonds and their then historically low yields were reduced to 25%.

In May 2021, DiCiurcio noted, “interest rates were off their rock-bottom lows and the equity market had rallied. Compared with a year earlier, our forecasts had gone up for bonds and down for equities, so our optimal portfolio had taken off the equity overweight.”

And in May 2022, with rates having risen significantly and equities having sold off again, expected 10-year returns for both asset classes were improved. “It’s not as simple as saying equities have sold off; why not take a bit more equity risk? Because bonds have gotten so much more attractive,” DiCiurcio said. Rather, the concept of the “efficient frontier”— the set of portfolios expected to provide the greatest return across various risk appetites—comes into sharper focus.

“The risky-asset decision is a relative one between stocks and bonds,” he said. “VAAM is based on the actual forecast and tells us how much to reward an asset class in an allocation based on market conditions.”

Most Viewed

Ready to invest? See how to open an account
Start with this step-by-step guide to opening a personal investment account, such as a general investing brokerage account or an IRA.
Perspective in a time of heightened volatility
Market woes continue, but history has shown that saying the course is usually the best route to success.
Investing in a high-inflation world
Vanguard CEO Tim Buckley shares his views on investing in a high-inflation world.
How to choose a college savings account
Why volatility and downturns are part of investing
Chief Economist Joe Davis explains why market volatility and downturns happen and why they’re part of investing.
Fueling the FIRE movement: Updating the 4% rule for early retirees
With updates based on Vanguard’s principles of investing success, the 4% rule can help FIRE investors achieve success in retirement.

All investing is subject to risk, including the possible loss of the money you invest.

Diversification does not ensure a profit or protect against a loss.

Investments in bonds are subject to interest rate, credit, and inflation risk.

Investments in stocks and bonds issued by non-U.S. companies are subject to risks including country/regional risk and currency risk. These risks are especially high in emerging markets.

Be aware that fluctuations in the financial markets and other factors may cause declines in the value of your account. 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.

About the Vanguard Capital Markets Model:

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.