Cap-weighting concentrates funds in whatever has already grown the most. Just a few stocks can dominate the index, and passive investors absorb that concentration automatically. Committees that select index constituents optimize for coverage, not performance.
Some skilled managers may be able to navigate a given market regime with excess performance. The difficulty is that regimes change, and managers who can adapt are rare.
Systematic investing reduces subjectivity, but can introduce a different concern: complexity. When even a model’s operators can’t fully explain its decisions, it becomes a black box. That’s a hard system to trust.
Every investment decision follows a defined, repeatable process. Stocks are selected by the model, not by instinct, and the same rules apply in every market environment.
We favor factors with decades of empirical support across markets and economic regimes. If it hasn’t been tested rigorously, it doesn’t enter the framework.
Each position carries the same allocation. No single stock dominates your returns, and no company is assumed to deserve more funds simply because it has a larger market capitalization.
Fewer inputs. Fewer assumptions. Fewer points of failure. We believe it is better to do something simple with exceptional precision than something complex with middling results.
In quantitative investing, complexity is common. Adding parameters, layering signals, and optimizing on recent historical data can make backtests look impressive. But complexity risks mistaking the noise of the past for the signal of the future.
Simple models are harder to build because they require genuine conviction in a small number of ideas. They demand that every input earn its place. And they must work not because they were engineered to match history, but because the economic logic behind them is sound.
Our models are deliberately simple and rigorously tested. Our backtests span over 35 years of individual stock data. By using a point-in-time dataset we avoid survivorship and hindsight bias. The results reflect what an investor would actually have experienced, not what looks best in retrospect.
Broad equity exposure driven by systematic factor selection and equal weighting. The most complete expression of the framework.
Broad equity exposure with a deliberate tilt toward value and quality. A well-established combination of factors with decades of empirical support.
A concentrated strategy emphasizing quality and growth. Designed to fit within a smaller portfolio allocation.
Equal weighting eliminates the structural problem of cap-weighted indices: overexposure to the largest and often most expensive stocks.
Adding a strategy with a return profile distinct from its benchmark reduces overall portfolio correlation. Using multiple managers with independent strategies reduces it further.
Our approach preserves your proxy voting rights, giving your board direct influence over corporate governance. For institutions with a mission, this means your portfolio can reflect the same values as your organization.
Because the portfolio is rebalanced monthly, new accounts may be invested immediately. There is no legacy positioning to inherit and no need to time an entry.
You can exclude individual securities or sectors that conflict with your organization’s mission, values, or donor intent. This lets endowments and foundations align their portfolio with their purpose.
Our models are built to be understood. Every holding, factor, and rebalance is explainable. Because we manage strategies in-house, your investment committee has access to the decision-makers.
Whether you manage investments through an investment committee, work with a consultant, or are exploring an outsourced model, our strategies are designed to integrate into your existing governance structure. We work with:
Learn more about our quantitative investment approach, including detailed strategy materials and historical performance.
