56a4627bb2
Foundation patch for the Forward-Return-Distribution head (SP20 P3). No new behavior — kernels arrive in the next commit (F.2). This commit just establishes the ISV vocabulary and structural dims so the kernel code can reference named slots/consts from day one. ISV slots 498-503 (RL_SLOTS_END bumped 498 → 504): * RL_FRD_LAMBDA_INDEX = 498 seed 0.5 * RL_FRD_LR_INDEX = 499 seed 1e-3 * RL_FRD_HORIZON_1_TICKS_INDEX = 500 seed 60.0 * RL_FRD_HORIZON_2_TICKS_INDEX = 501 seed 300.0 * RL_FRD_HORIZON_3_TICKS_INDEX = 502 seed 1800.0 * RL_FRD_BUCKET_RANGE_SIGMA_INDEX = 503 seed 3.0 (±3σ) Bootstraps written via the existing isv_constants table in IntegratedTrainer::new — same path as the SP20 P5 trail bounds. No HtoD path opened (rl_isv_write does device-side scalar writes). Structural consts (crates/ml-alpha/src/rl/common.rs): * FRD_HIDDEN_DIM = 64 (MLP hidden layer width) * FRD_N_HORIZONS = 3 (h1/h2/h3 forward returns) * FRD_N_ATOMS = 21 (return-bucket atoms per horizon) Atom count is the only structural compile-time dim per §0.1 of the SP20 spec; range_σ is ISV-driven (slot 503) so the head can adapt as realised σ drifts.
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.