jgrusewski 26be2b8abe design(policy-quality): revision 2 — full 4-track V7 + outside-the-box
Addresses critique from second self-review:

1. SCOPE GAP fixed: spec now covers all 4 V7 categories the user asked
   for. Added Track 3 (controllers) and Track 4 (exploration) with their
   own smoke tests (controller_activity, exploration_coverage) and
   HEALTH_DIAG fields. Previous version only had action-space + reward.

2. H1-H5 expanded to H1-H10 with 5 new codebase-specific hypotheses:
   - H6: Regime-adaptive trailing stop closing Full-positions early
   - H7: VSN / NoisyNets masking magnitude features
   - H8: Target tau too slow for magnitude propagation
   - H9: Data genuinely favors Quarter (no bug, delete magnitude branch)
   - H10: Entropy regularization + argmax tie ordering bias

3. H3 REFRAMED from "Kelly bug" to design critique — Kelly as hard
   multiplier vs soft gate. Fix sketch updated to offer replacement.

4. Feature branch + tag strategy replaces "single branch" containment.
   feat/policy-quality isolates work from main until Phase 4 merge via
   PR. git tag policy-quality-baseline gives named rollback anchor.

5. SURROGATE-NOISE CHECK added as MANDATORY validation gate — catches
   look-ahead/leakage bugs that would otherwise produce false-positive
   edges. Permanent smoke artifact.

6. Validation gate restructured: B + surrogate-noise MANDATORY;
   A criteria soft; controller-activity soft. Partial success path
   explicit per-gate.

7. Risk register expanded — added scenarios for B-mandatory failure
   (feat branch stays unmerged), all-10-hypotheses-REJECTED (fall back
   to H9 delete-branch), surrogate-noise failure (halt spec, open
   diagnostic spec), multi-load-bearing-controllers (tech debt doc).

8. Budget corrected to 5.5-6.5 hrs L40S (was underestimated 3.5-4),
   with per-track breakdown.

Spec now: 464 lines, 10 sections, covers 4 V7 tracks × ~10 hypotheses
+ 8 reward terms + 7 controllers + 5 exploration mechanisms = ~30
audit items total.
2026-04-21 20:39:34 +02:00

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
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Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
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