jgrusewski 0c8b4b5608 refactor(per-horizon): N_HORIZONS 5→3 — ml-backtesting full propagation
Source migration:
- crates/ml-backtesting/src/lob/mod.rs:5 + policy/mod.rs:18: local
  const N_HORIZONS 5→3 via re-export from ml_alpha::heads::N_HORIZONS
  (single source of truth across crates)
- crates/ml-backtesting/src/sim/mod.rs:1751,1773,1784: [IsvKellyStateHost; 5]
  array literals → ; N_HORIZONS]
- crates/ml-backtesting/cuda/lob_state.cuh:9: #define N_HORIZONS 5→3
  (this triggers cubin rebuild of decision_policy + 4 other ml-backtesting
  kernels that #include this header)

Test migration (8 test files + 2 JSON fixtures):
- threshold_and_cost.rs, decision_floor_coldstart.rs, parallel_sim_
  correctness.rs, stop_controller.rs (37+10+1 broadcast_alpha calls),
  lob_sim_integrated_fuzz.rs, lob_sim_fixtures.rs: hardcoded [f32; 5]
  alpha-probs and [IsvKellyStateHost; 5] arrays → N_HORIZONS-sized via
  std::array::from_fn or [v; N_HORIZONS] literals
- trainer_parity.rs:34 + ring3_replay.rs:47: horizons literal
  [30,100,300,1000,6000] → ml_alpha::heads::HORIZONS
- fixtures/decision_alpha_buy_close.json + decision_program_h4_only.json:
  5-element warm_start_isv_kelly / alpha_probs / expected_isv_kelly_after
  trimmed to 3 elements; active horizon relocated to N_HORIZONS-1

Library lib-test rewrite (per pearl_tests_must_prove_not_lock_observations):
- crates/ml-backtesting/src/policy/mod.rs:197-233: lib tests
  default_strategy_has_5_horizon_leaves + ..._flattens_to_5_emits...
  renamed to N_HORIZONS-parametric form (observed-value 5 and 7
  were bug-locks).

cargo check -p ml-backtesting --all-targets: clean.
cargo test -p ml-backtesting --lib: 33 passed.
cargo test -p ml-backtesting --tests (non-CUDA, non-fixture-data): 2 passed,
53 ignored (CUDA-gated or FOXHUNT_TEST_DATA-gated).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 01:37:23 +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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Cuda 7.7%
Python 1.3%
Shell 1.1%
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