The Betterment Core portfolio strategy

I. Introduction

Betterment builds investment portfolios designed to help you make the most of your money so you can live the life you want. 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 Core portfolio strategy contains 101 individualized risk levels (each with a different percentage of the portfolio invested in stocks vs. bonds, informed by your financial goals, time horizon and risk tolerance), in part, because that level of granularity in allocation management provides the flexibility to align to multiple goals with different timelines and circumstances.

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 any given feasible level of risk. The objective of most long-term portfolio strategies is to maximize return for a given level of risk, which 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.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 maximize expected return given an expected risk level or, equivalently, minimize expected risk given an expected return.

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

Asset Classes Selected for Betterment’s Core Portfolio Strategy

III. Portfolio Optimization

As an asset manager, we fine-tune the investments our clients hold with us, seeking to maximize return potential for the appropriate amount of risk each client can tolerate. We base this effort on a foundation of established techniques in the industry and our own rigorous research and analysis.

While most asset managers offer a limited set of model portfolios at a defined risk scale, the Betterment Core 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 Core portfolio strategy to contain 101 different risk levels.

Optimizing Portfolios

Modern Portfolio Theory requires estimating variables such as expected-returns, covariances, and volatilities to optimize for portfolios that sit along an efficient frontier. We refer to these variables as capital market assumptions (CMAs), and they provide quantitative inputs for our process to derive favorable asset class weights for the portfolio strategy. 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.⁵ 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.⁴

In order to complete the equation above and compute the expected returns using reverse optimization, we need the covariance matrix as an input. This matrix mathematically describes the relationships of every asset with each other as well as the volatility risk of the assets themselves. 

In another more recent evolution of our investment process, we also attempt to increase the robustness of our CMAs by averaging in the estimates of expected returns and volatilities published by large asset managers such as BlackRock, Vanguard, and State Street Global Advisors. We weight the contribution of their figures to our final estimates based on our judgment of the external provider’s methodology.

Constrained optimization for stock-heavy portfolios

After formulating our CMAs for each of the asset classes we favor for inclusion in the Betterment Core portfolio strategy, we then solve for target portfolio allocation weights (the specific set of asset classes and the relative distribution among those asset classes in which a portfolio will be invested), with the range of possible solutions constrained by limiting the deviation from the composition of the custom benchmark. To robustly estimate the weights that best balance risk and return, we first generate several thousand random samples of 15 years of expected returns for the selected asset classes based on our latest CMAs, assuming a multivariate normal distribution. For each sample of 15 years of simulated expected return data, we find a set of allocation weights subject to constraints that provide the best risk-return trade-off, expressed as the portfolio’s Sharpe ratio, i.e., the ratio of its return to its volatility. Averaging the allocation weights across the thousands of return samples gives a single set of allocation weights optimized to perform in the face of a wide range of market scenarios (a “target allocation”).

The constraints are imposed to make the portfolio weights more benchmark-aware by setting maximum and minimum limits to some asset class weights. These constraints reflect our judgment of how far the composition of geographic regions within the portfolio’s stock and bond allocations should differ from the breakdown of the indices used in the benchmark before the risk of significantly varied performance between the portfolio strategy and the benchmark becomes untenable. For example, the share of the portfolio’s stock allocation assigned to international developed stocks should not be profoundly different from the share of international developed stocks within the MSCI ACWI. We implement caps on the weights of emerging market stocks and bonds, which are often projected to have high returns in our CMAs, and set minimum thresholds for U.S. stocks and bonds. This approach not only ensures our portfolio aligns more closely with the benchmark, but it also mitigates the risk of disproportionately allocating to certain high expected return asset classes.

Constrained optimization for bond-heavy portfolios 

For versions of the Core portfolio strategy that have more than or equal to 60% allocation to bonds, the optimization approach differs in that expected returns are maximized for target volatilities assigned to each risk level. These volatility targets are determined by considering the volatility of the equivalent benchmark. Manually established constraints are designed to manage risk relative to the benchmark, instituting a declining trend in emerging market stock and bond exposures as stock allocations (i.e., the risk level) decreases. Meaning that investors with more conservative risk tolerances have reduced exposures to emerging market stocks and bonds because emerging markets tend to have more volatility and downside-risk relative to more established markets. Additionally, as the stock allocation percentage decreases, we taper the share of international and U.S. aggregate bonds within the overall bond allocation, and increase the share of short-term Treasury, short-term investment grade, and inflation-protected bonds. This reflects our view that investors with more conservative risk tolerances should have increased exposure to short-term Treasury, short-term investment grade, and inflation-protected bonds relative to riskier areas of fixed income.

The lower available risk levels of the Core portfolio strategy demonstrate capital preservation objectives, as the shorter-term fixed income exposures likely possess less credit and duration risk. Clients invested in the Core portfolio at conservative allocation levels will likely therefore not experience as significant drawdowns in the event of waves of defaults or upward swings in interest rates. Inflation-protected securities also help buffer the lower risk levels from upward drafts in inflation.

IV. Tax Management Using Municipal Bonds

V. The Value Tilt Portfolio Strategy

Existing Betterment customers may recall that historically the Core portfolio strategy held a tilt to value companies, or businesses that appear to be potentially undervalued based on metrics such as price to earnings ratios. The latest iteration of the Core portfolio strategy, however, has deprecated this explicit tilt that was expressed via large-, mid-, and small-capitalization U.S. value stock ETFs, while maintaining some exposure to value companies through broad market U.S. stock funds. 

We no longer favor allocating to value stock ETFs within the Core portfolio strategy in large part as a result of our adoption of a broad market benchmark, which highlights the idiosyncratic nature of such tilts, sometimes referred to as “off benchmark bets.” We believe our chosen benchmark that represents stocks through the MSCI ACWI, which holds a more neutral weighting to value stocks, more closely aligns with the risk and return expectations of Betterment’s diverse range of client types across individuals, financial advisors, and 401(k) plan sponsors. Additionally, as markets have grown more efficient and value factor investing more popularized, potentially compressing the value premium, we have a marginally less favorable view of the forward-looking, risk-adjusted return profile of the exposure. 

That being said, we have not entirely lost conviction in the research supporting the prudence of value investing. The value factor’s deep academic roots drove decisions to incorporate the value tilt into Betterment’s portfolios from the company’s earliest days. For investors who wish to remain invested in a value strategy, we have added the Value Tilt portfolio strategy, a separate option from the Core portfolio strategy to our investing offering. The Value Tilt portfolio strategy maintains the Core portfolio strategy’s global diversification across stocks and bonds while including a sleeve within the stock allocation of large-, mid-, and small-capitalization U.S. value funds.

We calibrated the size of the value fund exposure based on a certain target historical tracking error to the backtested performance of the latest version of the Core portfolio strategy. Based on this approach, investors should expect the Value Tilt portfolio strategy to generally perform similarly to Core, with the potential to under- or outperform based on the return of U.S. value stocks. With the option to select between the Value Tilt portfolio strategy or a Core now without an explicit allocation to value, the investment flexibility of the Betterment platform has improved.

VI. Innovative Technology Portfolio Strategy

VII. Conclusion

VIII. Citations