Butterfly works across disciplines that rarely meet. Here is each field in plain terms — what it studies, and what it brings to the others.
The core of the studio: turning academic finance into working models for pricing, portfolio construction and investment strategy. We favour methods that are documented, testable and transparent over black boxes.
Reading the wider landscape — growth, inflation, rates and cycles — so that a strategy is aware of the weather it operates in. Macro context is what keeps a good model from being right in theory and wrong in practice.
Nothing ships without solid engineering. We build with robust, well-understood technologies so that a promising idea becomes a reliable tool — fast enough to use, simple enough to trust, and built to evolve.
Where algorithms meet data. From classical numerical analysis to modern machine learning, this is how complexity becomes an actionable signal — used carefully, and always checked against reality.
Distributed ledgers change what is possible in finance — from transparent settlement to programmable assets. We study where the technology genuinely helps, and build crypto tools on that honest basis.
Techniques born in engineering for pulling a clean signal out of noise. Applied to markets and to sensor data alike, they turn raw, messy series into something you can reason about.
The furthest field from finance — and the point of the studio. Decoding and analysing molecular data uses the same numerical and AI methods as our financial work, and pushes them in new directions.
Each field above ends up in a tool you can use. See how the ideas take shape as products.