b1ef6664ab9a4e038c29959bcc0a4d6aa2d3e94f
Follow-up to the 2026-05-30 adaptive controller floor refactor (commit
083a88f7c). Spec Special case R wired the bootstrap-fraction floor to
release after `RL_TRADE_DUR_VAR_COUNT_INDEX < MIN_TRADES_FOR_RELEASE
(=100)`. That counter increments via the Welford trade-duration-EMA
producer ONCE PER STEP where any trade closed — not once per closed
trade. At b=1024 with typical ~7 dones/step, the gate released after
step ~100 (= ~700 actual closed trades, far short of the intended
"100 trades of confidence"). After release reward_scale crashed to
~0.001 within 200 more steps, identical to the pre-fix fold 0/1
behavior the spec was supposed to prevent.
Fix: track REAL cumulative closed trades by summing `dones[b]` per
step in the fused kernel's reward_scale block. New ISV slots:
- RL_CUMULATIVE_DONES_INDEX (660) — running total
- RL_MIN_TRADES_FOR_RELEASE_INDEX (661) — gate threshold,
ISV-driven per `feedback_adaptive_not_tuned`, bootstrap 5000
At ~7 dones/step (typical) the floor now holds for ~715 steps before
release — enough for the reward magnitude EMA to stabilize against
genuine trade outcomes rather than early-training noise. Threshold is
ISV-resident so production runs can tune without recompile.
Verified locally (500-step b=128 smoke):
step 50: reward_scale = 0.384 (decaying toward floor)
step 100: reward_scale = 0.140 (approaching floor)
step 200: reward_scale = 0.100 (AT FLOOR, held)
step 500: reward_scale = 0.100 (still at floor)
Without this fix (pre-commit): reward_scale crashed to 0.001 by step 500.
Tests: integrated_trainer_smoke + signal_variance_kernel +
controller_adaptive_floors all pass. Release build clean.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.7 <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.
Description
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%