The Betterment Portfolio Strategy

We continually improve the portfolio strategy over time in line with our research-focused investment philosophy.


  1. Introduction
  2. Global Diversification and  Asset Allocation
  3. Portfolio Optimization
  4. Tax Management Using Municipal Bonds
  5. Conclusion
  6. Citations

I. Introduction

Betterment has a singular objective: to help you make the most of your money, so that you can live better. Our investment philosophy forms the basis for how we pursue that objective: Betterment uses real-world evidence and systematic decision-making to help increase our customers’ wealth.

In building our platform and offering individualized advice, Betterment’s philosophy is actualized by our five investing principles. Regardless of one’s assets or specific situation, Betterment believes all investors should:

  1. Make a personalized plan.
  2. Build in discipline.
  3. Maintain diversification.
  4. Balance cost and value.
  5. Manage taxes.

To align with Betterment’s investing principles, a portfolio strategy must enable personalized planning and built-in discipline for investors. The Betterment Portfolio Strategy is comprised of 101 individualized portfolios, in part, because that level of granularity in allocation management provides the flexibility to align to multiple goals with different timelines and circumstances. 

In this in-depth guide to the Betterment Portfolio Strategy, our goal is to demonstrate how the Betterment Portfolio Strategy, in both its application and development, contributes to how Betterment carries out its investing principles. When developing a portfolio strategy, any investment manager faces two main tasks: asset class selection and portfolio optimization. How we select funds to implement the Betterment Portfolio Strategy is also guided by our investing principles, and is covered separately in our Investment Selection Methodology paper.

II. Global Diversification and Asset Allocation

An optimal asset allocation is one that lies on the efficient frontier, which is a set of portfolios that seek to achieve the maximum objective for the lowest amount of risk. The objective of most long-term portfolio strategies is to maximize return, while the associated risk is measured in terms of volatility—the dispersion of those returns. In line with our investment philosophy of making systematic decisions backed by research, Betterment’s asset allocation is based on a theory by economist Harry Markowitz called Modern Portfolio Theory, as well as subsequent advancements based on that theory 1.

A major tenet of Modern Portfolio Theory is that any asset included in a portfolio should not be assessed by itself, but rather, its potential risk and return should be analyzed as a contribution to the whole portfolio. Modern Portfolio Theory seeks to optimize maximizing expected returns and minimizing expected risk.

 Other forms of portfolio construction may legitimately pursue other objectives, such as optimizing for income, or minimizing loss of principal.

However, our portfolio construction goes beyond traditional Modern Portfolio Theory in five important ways:

  • Estimating forward looking returns
  • Estimating covariance
  • Tilting specific factors in the portfolio
  • Accounting for estimation error in the inputs
  • Accounting for taxes in taxable accounts

Asset Classes Selected for the Betterment Portfolio Strategy

The Betterment Portfolio Strategy’s asset allocation starts with a universe of investable assets. Leaning on the work of Black-Litterman, the universe of investable assets for us is the global market portfolio 2. To capture the exposures of the asset classes for the global market portfolio, Betterment evaluates available exchange-traded funds (ETFs) that represent each class in the theoretical market portfolio. We base our asset class selection on ETFs because this aligns portfolio construction with our investment selection methodology. Betterment’s portfolios are constructed of the following asset classes:


  • U.S. Equities
  • International developed market equities
  • Emerging market equities


  • U.S. short-term treasury bonds
  • U.S. inflation protected bonds
  • U.S. investment grade bonds
  • U.S. municipal bonds
  • International developed market bonds
  • Emerging market bonds

We select U.S. and international developed market equities as a core part of the portfolio. Historically, equities exhibit a high degree of volatility, but provide some degree of inflation protection. Even though significant historical drawdowns, such as the global financial crisis of 2008, demonstrate the possible risk of investing in equities, longer-term historical data and our forward expected returns calculations suggest that developed market equities remain a core part of any asset allocation aimed at achieving positive returns. This is because, over the long term, developed market equities have tended to outperform bonds on a risk-adjusted basis.

To achieve a global market portfolio, we also include equities from less developed economies, called emerging markets. Generally, emerging market equities tend to be more volatile than U.S. and international developed equities. And while our research shows high correlation between this asset class and developed market equities, their inclusion on a risk-adjusted basis is important for global diversification.

Note that Betterment’s portfolios exclude frontier markets, which are even smaller than emerging markets, due to their widely varying definition, extreme volatility, small contribution to global market capitalization, and cost to access.

The Betterment Portfolio Strategy also includes bond exposure because historically, bonds have a low correlation with equities, and they remain an important way to dial down the overall risk of a portfolio. To promote diversification and leverage various risk and reward tradeoffs, the Betterment Portfolio Strategy includes exposure to several asset classes of bonds.

Asset Classes Excluded from the Betterment Portfolio Strategy

While Modern Portfolio Theory would have us craft the Betterment Portfolio Strategy to represent the total market, including all available asset classes, we exclude some asset classes whose cost and/or lack of data outweighs the potential benefit gained from their inclusion in the Portfolio Strategy.

The Betterment portfolio construction process excludes private equity, commodities, and natural resources asset classes. Specifically, while commodities represent an investable asset class in the global financial market (it is however available as an asset class as part of Flexible Portfolio if investors wish to create their own custom portfolio), we have excluded commodities ETFs from the Betterment Portfolio Strategy because of their low contribution to a global stock/bond portfolio's risk-adjusted return.

In addition, real estate investment trusts (REITs), which tend to be well marketed as a separate asset class, are not explicitly included in the Portfolio Strategy (but is also available as part of the Flexible Portfolio to create custom portfolios). The Betterment Portfolio Strategy does however provide exposure to real estate, but as a sector within equities. Adding additional real estate exposure by including a REIT asset class would overweight the Portfolio Strategy’s exposure to real estate relative to the overall market.

III. Portfolio Optimization

While asset selection sets the stage for a globally diversified portfolio strategy, we further optimize the Betterment Portfolio Strategy by tilting the portfolio strategy to drive higher return potential.

While most asset managers offer a limited set of model portfolios at a defined risk scale, the Betterment Portfolio Strategy is designed to give customers more granularity and control over how much risk they want to take on. Instead of offering a conventional set of three portfolio choices—aggressive, moderate, and conservative—our portfolio optimization methods enable the Betterment Portfolio Strategy to contain 101 different portfolios.

Optimizing Portfolios

Modern Portfolio Theory requires estimating returns and covariances to optimize for portfolios that sit along an efficient frontier. While we could use historical averages to estimate future returns, this is inherently unreliable because historical returns do not necessarily represent future expectations. A better way is to utilize the Capital Asset Pricing Model (CAPM) along with a utility function which allows us to optimize for the portfolio with a higher return for the risk that the investor is willing to accept.

Computing Forward-Looking Return Inputs

Under CAPM assumptions, the global market portfolio is the optimal portfolio. Since we know the weights of the global market portfolio and can reasonably estimate the covariance of those assets, we can recover the returns implied by the market 3. This relationship gives rise to the equation for reverse optimization:

μ = λ Σ ωmarket

Where μ is the return vector, λ is the risk aversion parameter, Σ is the covariance matrix, and ωmarket is the weights of the assets in the global market portfolio 4. By using CAPM, the expected return is essentially determined to be proportional to the asset’s contribution to the overall portfolio risk.

It’s called a reverse optimization because the weights are taken as a given and this implies the returns that investors are expecting. While CAPM is an elegant theory, it does rely on a number of limiting assumptions: e.g., a one period model, a frictionless and efficient market, and the assumption that all investors are rational mean-variance optimizers 5.

In order to complete the equation above and compute the expected returns using reverse optimization, we need the covariance matrix as an input. 

The covariance matrix mathematically describes the relationships of every asset with each other as well as the volatility risk of the assets themselves. Our process for estimating the covariance matrix aims to avoid skewed analysis of the conventional historical sample covariance matrix and instead employs Ledoit and Wolf’s shrinkage methodology, which uses a linear combination of a target matrix with the sample covariance to pull the most extreme coefficients toward the center, which helps reduce estimation error 6.

Tilting the Betterment Portfolios based on the Fama-French Model

Academic research also points to persistent drivers of returns that the market portfolio doesn’t fully capture. A framework known as the Fama-French Model demonstrates how equity returns are driven by three factors: market, value, and size 7.

The underlying asset allocation of the Betterment Portfolio Strategy ensures the market factor is incorporated, but to gain higher returns from value and size, Betterment tilts the portfolios. For the actual mechanism of tilting, we turn to the Black-Litterman model.

Black-Litterman starts with our global market portfolio as the asset allocation that an investor should take in the absence of views on the underlying assets. Then, using the Idzorek implementation of Black-Litterman, the Betterment Portfolio Strategy is tilted based on the level of confidence we have for our views on size and value 8. These views are computed from historical data analysis, and our confidence level is a free parameter of the implementation.

Tilts are expressed, taking into account the constraints imposed by the liquidity of the underlying funds.

Monte Carlo Simulations

Betterment uses Monte Carlo simulations to predict alternative market scenarios. By doing an optimization of the Portfolio Strategy under these simulated market scenarios, Betterment averages the weights of asset classes in each scenario, which provides a more robust estimate of the optimal weights. Betterment believes this secondary optimization analysis alleviates the portfolio construction’s sensitivity to returns estimates and leads to more diversification and expected performance over a broader range of potential market outcomes.

Thus, through our method of portfolio optimization, the Betterment Portfolio Strategy is weighted based on the tilted market portfolio, based on Fama-French, averaged by the weights produced by our Monte Carlo simulations. This portfolio construction process gives us a portfolio strategy designed to be optimal at any risk level for not just diversification and expected future value, but also ideal for good financial planning and for managing investor behavior.

IV. Tax Management Using Municipal Bonds

For investors with taxable accounts, portfolio returns may be further improved on an after-tax basis by utilizing municipal bonds. This is because the interest from municipal bonds is exempt from federal income tax. To take advantage of this, the Betterment Portfolio Strategy in taxable accounts is also tilted toward municipal bonds because interest from municipal bonds is exempt from federal income tax, which can further optimize portfolio returns. Other types of bonds remain for diversification reasons, but the overall bond tax profile is improved by tilting towards municipal bonds. For investors in states with the highest tax rates—New York and California—Betterment can optionally replace the municipal bond allocation with a more narrow set of bonds for that specific state, further saving the investor on state taxes. Betterment customers who live in NY or CA can contact customer support to take advantage of state specific municipal bonds.


After setting the strategic weight of assets in the Betterment Portfolio Strategy, the next step in implementing the strategy is Betterment’s investment selection process, which selects the appropriate ETFs for the respective asset exposure in a low-cost, tax-efficient way. In keeping with our philosophy, that process, like the portfolio construction process, is executed in a systematic, rules-based way, taking into account the cost of the fund and the liquidity of the fund.

Beyond ticker selection is our established process for allocation management—how we advise downgrading risk over time—and our methodology for automatic asset location, which we call Tax Coordination. Finally, our overlay features of automated rebalancing and tax-loss harvesting are designed to be used to help further maximize individualized, after-tax returns.

Together these processes put our principles into action, to help each and every Betterment customer maximize value while invested at Betterment and when they take their money home.


1 Markowitz, H., "Portfolio Selection".The Journal of Finance, Vol. 7, No. 1. (Mar., 1952), pp. 77-91.
2 Black F. and Litterman R., Asset Allocation Combining Investor Views with Market Equilibrium, Journal of Fixed Income, Vol. 1, No. 2. (Sep., 1991), pp. 7-18. Black F. and Litterman R., Global Portfolio Optimization, Financial Analysts Journal, Vol. 48, No. 5 (Sep. - Oct., 1992), pp. 28-43.
3 Litterman, B. (2004) Modern Investment Management: An Equilibrium Approach.

Note that that the risk aversion parameter is a essentially a free parameter.


Ilmnen, A., Expected Returns.


Ledoit, O. and Wolf, M., Honey, I Shrunk the Sample Covariance Matrix, Olivier Ledoit & Michael Wolf.


Fama, E. and French, K., (1992). "The Cross-Section of Expected Stock Returns". The Journal of Finance.47 (2): 427.


Idzorek, T., A step-by-step guide to the Black-Litterman Model.