About Altus Labs
Quantitative Infrastructure for Non-Linear Market Dynamics
We build systematic infrastructure for measuring endogenous market stress—addressing the fundamental gap between how portfolios are constructed and how wealth actually compounds over time.
The Structural Void
Why Current Approaches Fall Short
Modern Portfolio Theory, Risk Parity, and traditional 60/40 allocations share a common characteristic: they tend to be pro-cyclical. These frameworks can increase leverage at exactly the point where systemic risk is elevated.
As options adoption and algorithmic passive investing increase, markets become prone to abrupt liquidity vacuums. Traditional allocations often lack explicit dynamic tail-risk hedging— they optimize for the middle of the distribution while the tails are where wealth is actually made and destroyed.
This creates a volatility feedback loop that can amplify drawdowns precisely when capital preservation matters most.
The Ergodicity Problem
Traditional finance optimizes for ensemble averages—what happens across many investors. But you experience a single sequence of returns over time. These are fundamentally different optimization targets.
Pro-Cyclical Construction
Risk parity and volatility targeting increase leverage when volatility is low and decrease it when volatility spikes—which may not align with what long-term compounding requires.
Transparency Gap
Many institutional-grade strategies come with high minimums, lock-up periods, and limited visibility into methodology. There's room for more transparent approaches.
Our Approach
Transparent Infrastructure
We're building systematic infrastructure that enables institutions and family offices to maintain full visibility and control over their convexity positioning—complementing existing portfolio approaches with explicit tail-risk awareness.
Geometric Optimization
We optimize for what matters: the geometric mean growth rate of your portfolio over time. This means prioritizing survival and avoiding catastrophic drawdowns over maximizing expected returns.
Endogenous Risk Detection
Self-organized criticality models identify the build-up of systemic stress before it manifests in price—detecting bubble formation, position crowding, and pre-correction tremors.
Full Reproducibility
Every signal, every backtest, every research output is anchored by a verifiable, version-controlled audit trail. Complete transparency in methodology.
Vision
Research-as-a-Service
Our long-term vision is to provide systematic convexity infrastructure as a service— enabling family offices and institutions to access institutional-grade quantitative research while keeping investment decisions in-house.
We're building tools and signal infrastructure that provides a convexity lens for portfolio construction—helping investors incorporate tail-risk awareness into their existing approaches.
The goal is broadening access to systematic stress detection and tail-risk management capabilities that can complement a wide range of investment strategies.
Platform Capabilities
Convexity Engine
SOC-based detection of endogenous market risk build-up
Signal Processing
Forward-looking probability distributions across timeframes
Backtesting Infrastructure
Institutional-grade validation with realistic friction costs
Deterministic Audit Trails
100% reproducibility across all volatility regimes