Core technology.
Trading infrastructure.

Statistical modeling & deep learning

Statistical modeling and deep learning turn market data into estimates of regime, direction and relative volatility.

Pricing & portfolio analytics

Derivatives pricing, volatility surfaces and scenario analysis connect option values, sensitivities and portfolio exposures.

Hidden-state inference

Hidden-state modeling, filtering, smoothing and parameter estimation for time series—with explicit convergence and numerical diagnostics.

Signal analysis

From Haar and Daubechies wavelets to synchrosqueezed transforms: adaptive decomposition, denoising and cross-asset coherence for batch and streaming analysis.

Options strategy analytics

Constructs and ranks options spreads with modeled probability of profit, expected value, stress loss and execution costs. Powers Spread Foundry.

Numerical computing

Correctly rounded core functions, machine-checked error bounds and SIMD kernels that preserve scalar results across supported platforms.

Market data normalization

Normalize provider-specific market events into a consistent data stream for analytics, recording and trading systems.

Deterministic replay & virtual time

Clock and replay building blocks for systems that need repeatable execution and testable time behavior.

Order matching

Deterministic order matching in Rust, with price-time priority, order-book state and replayable execution.

Trading runtime

Run your strategy with risk admission, order lifecycle management, recording and broker feedback.