5ea5aa9b8e
Lifts the Phase 2 caps from sentinel-driven cold-start (5.0/-10.0
fixed) to p99(|step_ret|) over Long/Short trade closes × 1.5 safety
factor with Wiener-optimal alpha blend. The Phase 2 consumer
(compute_sp18_hold_opportunity_cost) sees producer-driven slots
[483]/[484] from epoch 1 onward; sentinel branch in the consumer
remains as the cold-start fallback path (zero-trade-close epoch ⇒
producer early-returns ⇒ slots stay at sentinel ⇒ consumer falls
through to the +5/-10 macro defaults — bit-identical to pre-Phase-3).
Mirrors SP14 P0-A reward_cap_update_kernel structural template with
three differences: (1) filter (is_close && step_ret != 0) — both
winners AND losers (the consumer needs the magnitude scale of *all*
Long/Short closes); (2) Welford-derived Wiener-α (slots [487..493))
replaces fixed α=0.01, with floor at WELFORD_ALPHA_MIN=0.4 per
pearl_wiener_alpha_floor_for_nonstationary (the policy-realised
distribution is intrinsically non-stationary as the policy adapts);
(3) bounds [0.5, 50.0] (vs. position-side [1.0, 50.0]).
Atomic single-commit per feedback_no_partial_refactor:
- crates/ml/src/cuda_pipeline/hold_reward_cap_update_kernel.cu (NEW)
- crates/ml/build.rs cubin manifest entry
- HoldRewardCapUpdateOps in gpu_aux_trunk.rs (new struct + impl)
- HOLD_REWARD_CAP_UPDATE_CUBIN static + struct field +
launch_hold_reward_cap_update method + constructor instantiation +
field-init in gpu_dqn_trainer.rs (5 sites)
- Per-epoch boundary launch in training_loop.rs right AFTER
launch_reward_cap_update (shared step_ret/trade_close source buffers,
independent ISV slot pairs)
- HEALTH_DIAG[N]: hold_reward_cap [pos={:.4} neg={:.4} fire_rate={:.4}]
- 3 GPU oracle tests (T5 producer-drives-slots, Pearl-A REPLACE,
no-closes preserves-isv) — all pass on local RTX 3050 Ti
- Phase 3 close-out sections in docs/sp18-wireup-audit.md and
docs/dqn-wire-up-audit.md
Pearls applied: feedback_no_atomicadd, pearl_first_observation_bootstrap,
pearl_wiener_optimal_adaptive_alpha, pearl_wiener_alpha_floor_for_nonstationary,
pearl_no_host_branches_in_captured_graph, pearl_symmetric_clamp_audit,
pearl_audit_unboundedness_for_implicit_asymmetry (NEG = -2 × POS at
producer time, single source of truth), feedback_isv_for_adaptive_bounds,
pearl_fused_per_group_statistics_oracle.
Validation: cargo check --workspace clean; 3 GPU oracle tests pass on
local RTX 3050 Ti; scripts/audit_sp18_consumers.sh --check exits 0
(no fingerprint drift in tracked sections).
Plan: docs/superpowers/plans/2026-05-08-sp18-reward-shape-hold-attractor.md
Phase 4-5 (B-leg target-net forward + q_next replacement) follows.
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.