Decades of research in behavioral finance and decision theory have reached a consistent conclusion: when it comes to repeated, high-stakes decisions, rules-based systems outperform human discretion. Not sometimes. Consistently, and often by a wide margin.
"The enemy of good decision-making is not ignorance. It is the illusion of expertise — the confidence that our judgment is better than the base rate."
The Evidence
The seminal work by Paul Meehl demonstrated that simple actuarial models outperformed clinical judgment across more than 130 studies. In finance, the evidence is equally compelling: factor-based models, systematic rebalancing rules, and algorithmic underwriting consistently match or beat experienced practitioners — with significantly less variance.
Why Discretion Fails
Human judgment fails in predictable ways: recency bias causes overweighting of recent data, availability bias distorts probability estimates, and overconfidence leads to underestimation of tail risk. In capital allocation, these biases are not occasional errors — they are systematic patterns that compound over time.
The Michie Lab Approach
Michie Lab was built on this premise. Every framework we design starts with a research question: what does the data say? We then build rules that encode the answer — removing judgment from the execution layer while preserving it at the design layer.
The result is a systematic process that performs consistently across market regimes, because it doesn't change based on how we feel about the market today. Discipline is not a personality trait. It is a process. And processes can be engineered.
For informational purposes only. Not investment advice. Michie Lab research is proprietary and primarily for internal use.