We don't just run regressions. We build high-fidelity simulations of financial market structure to diagnose endogenous risk.
Core Discipline
Standard risk models (Value-at-Risk) assume normal distributions and continuous liquidity. Our research focuses on Endogenous Phase Transitions; the moments where the market structure itself changes state (e.g., from liquid to frozen).
We utilize Dissipative Systems Theory and Thermodynamic Hamiltonians to map the high-dimensional state of the order book into a single diagnostic signal: the Instability Index (Λ).
Data Infrastructure
A theory is only as good as its data. We maintain a proprietary warehouse of high-fidelity market data, enabling us to reconstruct the "Atomic State" of the market at any given second.
High-Performance Computing
Calculating the implied volatility surface for 500 assets across 7 years requires solving over 35 million non-linear equations. We don't use Excel.
Our lab utilizes a vectorized local stack (DuckDB, Polars) and MinIO to perform high-throughput Black-Scholes inversion. By optimizing for SIMD instructions rather than raw cloud scale, we achieve institutional-grade backtesting speeds on commodity hardware.
CatInCloud Labs partners with Funds, Exchanges, and Data Vendors to solve hard structural problems.
We are currently accepting inquiries for Data Grants (in-kind support) and Sponsored Development of the Instability Index.