69b8fdb61a
Per spec §9.2 (3.5.5) post-amendment-2: replaces non-existent episode-level metadata with per-bar signal that fires when dd_pct(t) < dd_pct(t-1) AND dd_pct(t-1) > DD_TRAJECTORY_FLOOR — i.e. transition is part of a recovery from non-trivial DD. PER sampler (Phase 3.5.5.b follow-up) will read this and weight: sampling_weight = base × (1 + RECOVERY_OVERSAMPLE_WEIGHT × signal) so recovery transitions get amplified gradient signal, completing the downward-spiral break-out chain (3.5.2 reward asymmetry → 3.5.3 cooldown gate → 3.5.4 plasticity → 3.5.5 PER recovery curriculum). 3 ISV slots: 439 DD_TRAJECTORY_DECREASING, 440 RECOVERY_OVERSAMPLE_ WEIGHT (2.0 sentinel; ISV-driven from current dd_pct in follow-up), 441 DD_TRAJECTORY_FLOOR (0.02 sentinel; ISV-driven 25th percentile of running dd_pct distribution in Phase 3.5.5.c follow-up per feedback_isv_for_adaptive_bounds). New sp15_dd_trajectory_prev_dd MappedF32Buffer (size 1) tracks prev_dd across kernel calls — mirrors Task 3.5.3 sp15_cooldown_ consecutive_losses non-ISV mapped-pinned scratch pattern. 4 fold-reset registry entries + dispatch arms (3 ISV + 1 scratch). Per established Phase precedent: kernel + launcher land first; PER sampler integration and 25th-percentile floor producer are purely additive follow-ups per feedback_no_partial_refactor. Anchor test 2.10 recovery_after_streak (Phase 2C / Phase 3.5 paired) — fully green via 3.5.2 + 3.5.4 + 3.5.5 combined. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.