Our Investment Strategy Group (ISG) is responsible for an ecosystem of sophisticated forecasting and modeling platforms that powers our research, underpins our investment and advice methodologies, supports our investment management teams, and advises product development and portfolio decisions.
The VCMM is a sophisticated financial simulation engine that powers our investment outlook and asset allocation decisions. It comprises three main elements: (1) a global, dynamic model that forecasts the drivers of long-term asset returns such as yield curves and equity market valuations; (2) attribution models that attribute asset returns to the drivers; and (3) a simulation engine to model the probability distribution of outcomes.
Accounting for current market conditions and the non-normality of asset returns, the VCMM’s asset-return simulation model blends quantitative statistical analysis and forward-looking return assumptions to generate distributions of global asset returns, cross-correlations, and volatility over long time horizons. The VCMM is a powerful tool for setting reasonable return expectations and evaluating the risk-and-return trade-offs inherent in portfolio decisions, such as the potential range of portfolio return outcomes and the probabilities of achieving return objectives or realizing downside-risk events.
The VCMM is grounded in the empirical view that the returns of various asset classes reflect the compensation investors receive for bearing different types of systematic risk. Using a long span of historical monthly data, the VCMM researchers establish a forward-looking equilibrium view of risk-free rates and market risk premia that helps determine long-term, forward-looking averages around which the near-term forecasts vary. Next, the VCMM estimates a dynamic statistical relationship among risk factors and asset returns. To account for what is left unexplained in the model, Monte Carlo simulation methods are used to simulate the uncertainty around modeled expectations. By explicitly accounting for important initial market conditions when generating its return distributions, the VCMM framework departs fundamentally from more basic Monte Carlo simulation techniques found in certain financial software.
The VAAM is employed to determine asset allocation among active, passive, and factor vehicles, simultaneously optimizing the three dimensions of risk/return trade-offs (alpha, systematic, and factor).
The model incorporates Vanguard’s forward-looking capital market return and client expectations for alpha risk and return to create portfolios consistent with the full set of investor preferences, solving for portfolio construction problems conventionally addressed in an ad hoc, suboptimal manner. It assesses risk and return trade-offs of portfolio combinations based on user-provided inputs such as risk preferences, investment horizon, and which asset classes and active strategies are to be considered.
The VLCM is a proprietary model for glide-path construction that can assist in the creation of custom investment portfolios for retirement as well as nonretirement goals.
Its utility-based framework incorporates behavioral finance considerations such as loss aversion and income shortfall aversion to evaluate the risk/return trade-offs of various asset allocation choices and analyze the probability of success and income sufficiency. Based on the VLCM’s framework, we find that risk-aversion levels are the dominant factor behind the broad stock-bond split in the glide path, affecting both the glide-path slope and the ending allocation.
Read our related white paper to learn more about the Vanguard Life-Cycle Model.
The VFAM is a proprietary model that evaluates multiple financial strategies simultaneously to recommend the optimal financial plan.
Incorporating data from VCMM and leveraging components of VAAM and VLCM, VFAM analyzes the complex interactions between various strategies, tax-lot accounting, advisory fees, Social Security benefits, life expectancy, and economic uncertainty. It doesn’t rely on arbitrary single values for inputs or assumptions but on a range of possibilities tailored for the individual or family. VFAM goes beyond other financial planning models, quantifying and ranking multiple integrated strategies by degree of potential added value.
Read our related white paper to learn more about the Vanguard Financial Advice Model.
Vanguard’s models work in concert. The VCMM’s global asset return, inflation, and interest rate projections are critical to our asset allocation methodology and financial planning recommendations.
Specifically, the probability distribution of projected asset returns and the cross-correlations among assets captured in the VCMM simulations illuminate the risk/return trade-offs of our portfolio construction decisions. These simulations feed into the VLCM, VAAM, and VFAM models, which seek to optimize expected investor utilities including glide-path construction, point-in-time asset allocation, active/passive investment, and financial planning decisions. The models find real-world application in investment products ranging from target-date funds to model and custom portfolios and in Vanguard’s advice service offers.
All investing is subject to risk, including the possible loss of the money you invest. 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.
Investments in target-date 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 work force. The fund will gradually shift its emphasis from more aggressive investments to more conservative ones based on its target date. An investment in target-date funds is not guaranteed at any time, including on or after the target date.
Vanguard does not, and will not, make any representations about whether a model portfolio is in the best interest of any investor; is not, and will not be, responsible for the determination of whether a model portfolio is in the best interest of any investor; and is not acting as an investment advisor to any investor
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. 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 client 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, such as the data presented in this paper, 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 future paths. Indeed, this is a key reason why we approach asset-return outlooks in a distributional framework.
The Vanguard Life-Cycle Model (VLCM)
The Vanguard Life-Cycle 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 set 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, savings 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.
Advice services are provided by Vanguard Advisers, Inc. ("VAI"), a federally registered investment advisor. VAI is a subsidiary of VGI and an affiliate of Vanguard Marketing Corporation ("VMC"). Neither VAI, VGI, nor VMC guarantees profits or protection from losses.