Jamie Lee’s passion for cooking extends beyond his kitchen adventures with his 6-year-old daughter and his love for smoking salmon on pellet grills. His day job on the Betterment Investing team mirrors the culinary world, where he and his colleagues refine investment strategies like a chef perfecting a recipe.
In this three-part series, we’ll take you behind the scenes to understand how Betterment constructs its low-cost, high-performing, and globally diversified portfolios. Today, we’ll focus on the high-level allocation of investments, a crucial aspect of portfolio construction.
The Science Behind a Safer Nest Egg
At the heart of Betterment’s investment strategy lies Modern Portfolio Theorydeveloped by the late American economist Harry Markowitz. This framework, which earned Markowitz a Nobel Prize in 1990, revolutionized how investors think about risk and diversification.
Diversification is key to reducing risk, and a significant part of building a portfolio is determining how much weight to give each asset class, a process known as asset allocation. This involves considering various factors such as large cap versus small cap companies, government versus corporate debt, and domestic versus international markets.
Global Perspectives and Market Interplay
Jamie Lee’s experiences growing up in South Korea during the late 1990s financial crisis shaped his career path. His interest in markets led him to pursue a PhD in statistics, and his global perspective is evident in Betterment’s approach to asset allocation.
The team starts with the hypothetical global market portfolioa snapshot of all investable assets worldwide. For instance, U.S. stocks represent about two-thirds of the value of all stocks, so they are weighted accordingly. This global perspective is crucial in projecting future returns and optimizing asset allocations.
Reverse Engineering Expected Returns
Betterment’s quantitative researchers, or quantsfocus on forward-looking forecasts rather than relying solely on historical performance. As Jamie Lee notes, past data is simply too unreliable. The biggest companies of the 1990s are vastly different from today’s market leaders, highlighting the need for a dynamic approach.
To build their forecasts, known as Capital Market AssumptionsBetterment uses a robust mathematical model. They simulate thousands of market paths, factoring in both their own forecasts and those of large asset managers like BlackRock. This Monte Carlo simulation style helps them find the optimal allocation for each path, which is then averaged to provide a single recommendation.
The outputs of this process are the asset allocation percentages that investors see in their portfolio details. These percentages are refreshed each year to ensure they remain optimal. However, the team’s work doesn’t end here. They still need to select the most cost-effective and efficient funds that provide the intended exposure to each relevant asset class.
Join us in the next part of this series as we delve into the process of selecting specific funds and how Betterment handles thousands of trades each day to keep customers’ portfolios in top shape.
