Setting realistic expectations

Vanguard Capital Markets Model® forecasts

May 16, 2024

This interactive graphic presents Vanguard’s expectations for the annualized performance of various equity and fixed income indexes, as well as commodities and the rate of U.S. inflation, over intermediate and long periods. Choose a forecast horizon, 10 or 30 years, and a chart or table view.

Note that in the chart view, hovering over a forecast range will reveal our median expectation for volatility. It also will show a range of 2 percentage points around the 50th percentile of the distribution of likely returns for equities and a 1-point range around the 50th percentile of likely returns for fixed income. More extreme returns are possible, as shown in the table view. 

We update our forecasts here on a quarterly basis. The forecasts below are as of March 31, 2024.

Mostly higher developed markets equity prices throughout the first quarter pushed valuations higher and forecasts somewhat lower. Higher developed markets sovereign bond yields in January and February outweighed flat to higher prices in March, pushing forecasts modestly higher uniformly. 

IMPORTANT: The projections or 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 the VCMM are derived from 10,000 simulations for each modeled asset class. Simulations are as of March 31, 2024. Results from the model may vary with each use and over time. For more information, please see the Notes section below.

Notes: These probabilistic return assumptions depend on current market conditions and, as such, may change over time.

Source: Vanguard Investment Strategy Group.

About the Vanguard Capital Markets Model

The asset-return distributions shown here are in nominal terms—meaning they do not account for inflation, taxes, or investment expenses—and represent Vanguard’s views of likely total returns, in U.S. dollar terms, over the next 10 or 30 years; such forecasts are not intended to be extrapolated into short-term outlooks. Vanguard’s forecasts are generated by the Vanguard Capital Markets Model® (VCMM) and reflect the collective perspective of our Investment Strategy Group. Expected returns and median volatility or risk levels—and the uncertainty surrounding them—are among a number of qualitative and quantitative inputs used in Vanguard’s investment methodology and portfolio construction process. Volatility is represented by the standard deviation of returns. 

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 VCMM is a proprietary financial simulation tool developed and maintained by Vanguard’s Investment Strategy Group. 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. 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 primary value of the VCMM is in its application to analyzing potential investor portfolios. VCMM asset-class forecasts—comprising distributions of expected returns, volatilities, and correlations—are key to the evaluation of potential downside risks, various risk-return trade-offs, and the diversification benefits of various asset classes. Although central tendencies are generated in any return distribution, Vanguard stresses that focusing on the full range of potential outcomes for the assets considered is the most effective way to use VCMM output.

The VCMM seeks to represent the uncertainty in the forecast by generating a wide range of potential outcomes. It is important to recognize that the VCMM does not impose “normality” on the return distributions, but rather is influenced by the so-called fat tails and skewness in the empirical distribution of modeled asset-class returns. Within the range of outcomes, individual experiences can be quite different, underscoring the varied nature of potential investment outcomes. Indeed, this is a key reason why we approach asset-return outlooks in a distributional framework. 

Indexes for VCMM simulations

The long-term returns of our hypothetical portfolios are based on data for the appropriate market indexes as of March 31, 2024. We chose these benchmarks to provide the most complete history possible, and we apportioned the global allocations to align with Vanguard’s guidance in constructing diversified portfolios.

Asset classes and their representative forecast indexes are as follows:

Equities
U.S. equities:
MSCI US Broad Market Index.
Global equities ex-U.S. (unhedged): MSCI All Country World ex USA Index.
Global ex-U.S. developed markets equities (unhedged): MSCI World ex-U.S. Equity Index.
Emerging markets equities (unhedged): MSCI Emerging Market Equity Index.
U.S. value: Stocks with a price/book ratio in the lowest one-third of the Russell 1000 Index.1
U.S. growth: Stocks with a price/book ratio in the highest one-third of the Russell 1000 Index.2
U.S. large-cap: Stocks with a market cap in the highest one-third of the Russell 1000 Index.3
U.S. small-cap: Stocks with a market cap in the lowest two-thirds of the Russell 3000 Index.4
U.S. REITs: FTSE/NAREIT US Real Estate Index.

Fixed income
U.S. aggregate bonds:
Bloomberg U.S. Aggregate Bond Index.
Global bonds ex-U.S. (hedged): Bloomberg Global Aggregate ex-USD Index.
U.S. Treasury bonds: Bloomberg U.S. Treasury Index.
U.S. intermediate credit: Bloomberg U.S. 5-10 Year Credit Bond Index.
U.S. high-yield corporate: Bloomberg U.S. High Yield Corporate Bond Index.
Emerging markets sovereign: Bloomberg Emerging Markets USD Sovereign Bond Index – 10% Country Capped.
U.S. TIPS: Bloomberg U.S. Treasury Inflation Protected Securities Index.
U.S. cash: U.S. 3-Month Treasury—constant maturity.
U.S. mortgage-backed securities: Bloomberg U.S. Mortgage Backed Securities Index.

Commodities: Bloomberg Commodity Index

U.S. inflation: Consumer Price Index for all Urban Consumers.

1 To generate our proxy for U.S. value, we sort the stocks in the index according to their price/book ratios and delete the highest two-thirds. We then market cap-weight the remaining portfolio of stocks.

2 To generate our proxy for U.S. growth, we sort the stocks in the index according to their price/book ratios and delete the lowest two-thirds. We then market cap-weight the remaining portfolio of stocks.

3 To generate our proxy for U.S. large-cap, we sort the stocks in the index according to their market capitalizations and delete the lowest two-thirds. We then market cap-weight the remaining portfolio of stocks.

4 To generate our proxy for U.S. small-cap, we sort the stocks in the index according to their market capitalizations and delete the highest one-third. We then market cap-weight the remaining portfolio of stocks.

A closer look

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