jgrusewski 4b2093a627 feat(sp5): Task A3 — Pearl 2 per-branch loss budget
Per-branch C51/IQN/CQL/Ens loss budgets driven by per-branch flatness =
var(Q[b]) / (σ[b]² + EPS_DIV). IQN dominates when flat, C51 yields
proportionally. CQL stays gated by existing regime_stability allocator.

Reads Q_VAR_PER_BRANCH (222..226 from Pearl 1's q_branch_stats) AND
NOISY_SIGMA (210..214 from Pearl 3 — must run AFTER both).

20 ISV slots (BUDGET_C51[190..194), BUDGET_IQN[194..198),
BUDGET_CQL[198..202), BUDGET_ENS[202..206), FLATNESS[206..210)).
StateResetRegistry: 5 new FoldReset entries.

producer_step_scratch_buf grew 111 → 131 (20 new outputs).
wiener_state_buf already at 543 (A1 sized for entire SP5 block).

Loss budget consumer migration deferred to Layer B.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-01 21:38:43 +02:00

Foxhunt

Production HFT trading system in Rust.

Architecture

The workspace contains 32 crates organized as follows:

Core Libraries (16)

Crate Purpose
trading_engine Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing
risk VaR, Kelly, circuit breakers, kill switches, compliance
risk-data Risk data types and shared structures
trading-data Trading data types
ml DQN Rainbow, PPO, TFT, Mamba2, ensemble inference
ml-data ML data types and feature definitions
data Market data ingestion and storage
backtesting Replay engine, strategy tester
adaptive-strategy Ensemble execution, microstructure analysis
common Shared types, resilience, error handling
storage S3 and local model storage
model_loader Model serialization and loading
market-data Market data feed handlers
database PostgreSQL access layer (SQLx)
config Configuration management
tli CLI commands and tooling

Services (8)

Service Purpose
backtesting_service gRPC backtesting service
broker_gateway_service FIX routing, broker connectivity
trading_service Core trading operations
ml_training_service Model training orchestration
data_acquisition_service Market data acquisition
trading_agent_service Autonomous trading agents
api_gateway gRPC API gateway with auth
web-gateway Axum REST + WebSocket gateway

Frontend

web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.

Building

# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace

# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib

# Clippy
SQLX_OFFLINE=true cargo clippy --workspace

ML Models

Four production model architectures on Candle v0.9.1 with CUDA:

  • DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
  • PPO -- Proximal Policy Optimization with GAE and LSTM policies
  • TFT -- Temporal Fusion Transformer for multi-horizon forecasting
  • Mamba2 -- State space model for sequence prediction

Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.

Infrastructure

  • Git: Gitea at git.fxhnt.ai (Tailscale-only), Scaleway DEV1-S
  • Observability: OpenTelemetry OTLP (env OTEL_EXPORTER_OTLP_ENDPOINT)
  • Database: PostgreSQL with SQLx offline mode for CI

License

Proprietary. All rights reserved.

Description
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Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
PLpgSQL 0.8%
Other 0.8%