Independent Research Lab
Industrial-era distributions don't describe modern markets. We publish portfolio, economic, and technology research that takes networks, fat tails, and path dependence seriously.
The Lens
Modern finance was built for an industrial economy. Linear price models, ensemble averages, mean-variance optimisation — the toolkit assumed an economy of physical assets, predictable cash flows, and well-behaved distributions. That economy is gone.
Today's markets run on networks: information networks, payment networks, attention networks. They compound non-linearly. They concentrate endogenous risk. They generate fat tails as a feature, not an anomaly. Classical tools systematically misprice this.
We work on what comes next. Three pillars hold the thesis together.
Markets optimise for ensemble averages — what happens across many parallel investors. You live a single sequence of returns. Geometric compounding, not arithmetic averages, is the only target that matters.
Value, risk, and stress flow through networks — positioning chains, payment systems, attention markets — not through individual securities. Models that treat assets as independent draws underweight every tail.
We approach financial systems as software engineers first. Engineered methodology, deterministic validation, and write-ups detailed enough that any technical reader with modern tools can reproduce the work.
What We Publish
Where we research, write, and document. Each portfolio publishes long-form notes, working papers, and engineering write-ups — at the level of detail required to reproduce the work.
Portfolio Research
Portfolio construction built on geometric compounding, not arithmetic averages. We research how volatility drag destroys wealth multiplicatively, why survival dominates return maximisation, and how convex payoff structures — using derivatives as a complexity moat — position for the tails where wealth is actually made and destroyed.
Economic Research
The global financial system is mid-upgrade — from industrial-era architecture to information-age infrastructure. We study the macro forces driving this transition: carry trade mechanics, monetary policy regime shifts, currency dynamics, and why traditional valuation models break down in network economies where uncertainty is irreducible.
Technology Research
Engineering write-ups for the systems behind the research: backtesting platforms (equity and options), volatility surface modelling, statistical validation methodology, and the infrastructure that supports it. Documented in enough depth that any technical reader, with modern tools, can rebuild it.
Research
Understanding the four types of market edges and a framework for smaller firms to design winnable games against larger, established players.
A framework for wealth creation through asymmetric positioning that prioritizes survival, geometric compounding, and convex portfolio design.
Why traditional valuation models fail in a network economy, and how simple heuristics outperform complex optimization under deep uncertainty.
Founder
Altus Labs was founded by Gunjeet Singh Mahal. A decade across major technology firms — P&L management, software engineering, and business value advisory — gives Labs a deliberately non-traditional lens on financial markets. We approach finance the way modern engineering teams approach hard problems: as systems to be measured, instrumented, and iterated.
The motivation is straightforward. Quantitative research on market microstructure, convexity, and complex-systems dynamics is typically locked behind institutional walls or scattered across academic papers that don't translate to practice. We publish at the intersection — rigorous enough to be useful, accessible enough to actually reach practitioners, engineers, and independent researchers.
Altus Labs Ltd is a UK private company. Not FCA-regulated. Nothing published constitutes investment advice or a solicitation for capital — it is research and educational content only.
Contact
We welcome enquiries from researchers, engineers, academics, fellow practitioners, and potential collaborators on research and methodology projects. We do not provide investment services or advice.
Location
London, United Kingdom
