e0e0abfb28
Per spec §9.2 (3.5.4) post-amendment-2 fix. TWO-STEP recovery:
1. Fire when DD_PERSISTENCE > PLASTICITY_PERSISTENCE_THRESHOLD AND
PLASTICITY_FIRED_THIS_FOLD == 0 → set fired flag, set warm-bars
counter to M_warm (default 200). [DEFERRED: reset last 10% of
advantage-head weights to Kaiming-He init via cuRAND.]
2. Per-bar warm-bars decrement; action-selection layer (consumer wiring
follow-up) reads max(COOLDOWN_BARS_REMAINING, PLASTICITY_WARM_BARS_
REMAINING) and forces Hold while > 0.
Weight-reset DEFERRED to Phase 3.5.4.b — kernel signature plumbed
(advantage_head_weights + n_weights) but no-op via (void) cast.
Documented in audit doc.
3 ISV slots: 436 PLASTICITY_FIRED_THIS_FOLD (debounce flag, resets at
fold boundary to re-arm next fold), 437 PLASTICITY_PERSISTENCE_THRESHOLD
(initial 100.0 sentinel; ISV-tracked from running mean of dd_persistence
in follow-up), 438 PLASTICITY_WARM_BARS_REMAINING (counter, OR-gates
with cooldown).
3 fold-reset registry entries + dispatch arms.
Three GPU oracle tests pass: fires-when-persistence-exceeds-threshold
(warm_bars [198, 200] post-fire-and-decrement), debounced-within-fold
(no re-fire when fired=1; warm decrements 50→49), no-fire-below-threshold.
Anchor test 2.22 plasticity_cooldown_interlock (Phase 2C / Phase 3.5
paired) — green via 3.5.4.b follow-up + action-selection consumer wiring.
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.