f3cb0c78c2
Critical review (combined fresh-eyes subagent + self-critique) flagged 14 issues. All addressed in this amendment. CRITICAL (blocks implementation): - §4.3 NEW: ISV slot allocation map [397..441) per phase, prevents parallel-dispatch ISV-table conflict (was: undefined, would break Approach B) - §4.4 NEW: Phase 2A ↔ Phase 1.2 ABI contract (LobBar struct as canonical contract, Phase 2A defines first; Phase 1.2 conforms). Restores parallelism dependency - §9.2 (3.5.4): plasticity injection now MANDATES cooldown engagement via PLASTICITY_WARM_BARS_REMAINING slot 438. NEW anchor test 2.22 plasticity_cooldown_interlock prevents random-tail-output retrigger loop - §9.2 (3.5.5): recovery curriculum replaced episode-level metadata (didn't exist in transition-level PER) with per-step DD_TRAJECTORY_ DECREASING signal — same goal, no PER restructure IMPORTANT (rework prevention): - §9.2 (3.5.3): cooldown K threshold from running mean of per-trade PnL (NOT variance — variance is LOW during streaks, would delay cooldown when needed) - §8.2 (3.5): Hold floor function form specified as bounded sigmoid with α/k/ε₀ ISV-driven; was "monotonic_inv_func" (undefined family) - §6.2: cost kernel per-side semantics explicit. Half-spread × side_ indicator at entry AND exit; commission_per_rt on close. Resolves round-trip vs per-side ambiguity - §6.2: OFI impact λ initial value 2e-4 + ISV refit methodology; was "empirical fit from MES historical" (hand-wavy) - §6.4: 8 baselines now mandate shared trunk forward; honest 15-25% overhead estimate (was 5-10%, optimistic) - §12.3: Q9 burn policy explicitly honor-system, not enforcement. Mitigations described as deterrents not enforcement - §10.6: Phase 4.5 thresholds CLI-config-driven with rationale, anchored empirically post-Phase-1 (was hardcoded > 1.0) NIT: - §9.2 (3.5.2): multiplier vs SP12 cap interaction explicit (applied BEFORE cap) - §8.2 (3.1): α=0.7 hardcoded → ISV-driven from grad ratio (was feedback_isv_for_adaptive_bounds violation) - §13: pearls reframed as candidates pending validation per discipline rule; pre-naming pressure removed Test count: 21 → 22 (added 2.22). Phase 2 LOC: 2000 → 2100. ISV_TOTAL_DIM: 396 → 441 post-SP15. All 14 issues addressed in spec text. Ready for user review. 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.