da2ad438ca
Ports two scope-complete fixes from the ml-alpha-phase-f-g-flawed reference branch: A7 fee model: - order_match.cu::submit_market_immediate gains 2 new kernel args (cost_per_lot_per_side, total_fees_per_b) mirroring the per-fill fee deduction in resting_orders.cu::apply_fill_to_pos:213-219. Fee deducts from pos.realized_pnl on EVERY fill (open, scale-in, counter); total_fees_per_b accumulates for telemetry. Single-writer-per-block plain += is safe — line 79 has `threadIdx.x != 0 → return` (feedback_no_atomicadd). - LobSimCuda::submit_market launch updated to pass the 2 new args. - LobSimCuda::upload_cost_per_lot_per_side host API lets callers configure ES-realistic fees (≈$1.25/contract/side). Default alloc_zeros = $0; production decision-policy path is unchanged (uploads its own cost via step_decision_with_latency). A8 loader pair API: - MultiHorizonLoader::next_sequence_pair returns (LabeledSequence, LabeledSequence) at adjacent anchors in the same source file. anchor_t sampled from [min_anchor, max_anchor−1) so anchor+1 also fits the upper-bound. Counts as ONE yielded sequence against n_max_sequences. - next_sequence_random and next_sequence_pair share a new private helper build_sequence_at(lf, anchor) -> LabeledSequence that contains the multi-resolution windowing logic. Single source of truth for the build (feedback_single_source_of_truth_no_duplicates). - next_sequence's caller-facing contract (random anchor, one sequence per call) is unchanged — alpha_train.rs supervised pipeline keeps working as-is. No new local tests this phase per the rebuild plan (R2): the fee deduction with default cost=0 is a no-op for existing callers, and G7 in R6 covers the with-fees path via a rebuilt reward_calibration test driving LobSimCuda directly (no LobEnv adapter). cargo check -p ml-alpha -p ml-backtesting + cargo build --tests on ml-backtesting both green; baseline test suite unaffected. 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.