jgrusewski 79578bbaf6 feat(fxcache): OFI_DIM 20→32, persist 12 real-math microstructure signals,
fix kernel-read gap

Adds 12 features to the DQN input pipeline:
 - 10 MicrostructureState::snapshot()[0..10] slots that were previously computed
   every bar and then discarded before reaching fxcache: ofi_trajectory,
   realized_variance, hawkes_intensity, book_pressure (weighted 10-level),
   spread_dynamics, aggression_ratio, queue_depletion_asymmetry,
   order_count_flux, intra_bar_momentum, regime_score.
 - 2 TLOB-novel slots derived directly from Mbp10Snapshot:
   order_count_imbalance = (Σbid_ct − Σask_ct) / Σ(bid_ct + ask_ct),
   microprice_residual = (weighted_mid − mid) / mid.

Also fixes a production gap: ofi_acceleration (slot 18) and
toxicity_gradient (slot 19) were persisted to fxcache via OFI_DIM=20
but the OFI embed kernel (experience_kernels.cu:6146-6173) only read
[0..18), silently discarding them every bar. Kernel extended to
consume full SL_OFI_DIM=32.

Dimension bumps (all 8-aligned):
  OFI_DIM          20 → 32
  FXCACHE_VERSION   4 → 5  (invalidates existing caches; regen via
                            precompute_features)
  STATE_DIM        96 → 104
  PADDING_DIM       4 → 0  (OFI expansion consumed padding, still 8-aligned)
  STATE_DIM_PADDED 128 (unchanged)
  OFI_EMBED_IN     18 → 32 (MLP input width; W/grad/Adam/m/v buffers
                            resized in lockstep via named constants)

fxcache regen results (175874 bars ES.FUT 2024-Q1):
  deltas_nonzero:       175781 / 175874  (99.9 percent)
  book_aggression:      102137 / 175874  (58.1 percent)
  microstructure[20-30): 175874 / 175874 (100 percent)
  tlob_novel[30-32):    133615 / 175874  (76.0 percent)

Compile status: SQLX_OFFLINE=true CARGO_INCREMENTAL=0 cargo check
  --workspace --tests passes cleanly (0 errors, pre-existing warnings
  only).

Test results:
  fxcache roundtrip (unit + integration): PASS (4+6 tests)
  magnitude_distribution smoke: ran through epoch 1 successfully
    (OFI_DIAG fires, state_dim=104 confirmed, feature_dim=74 in
    validation kernel); epoch 2 OOM on local RTX 3050 Ti (4 GB) —
    expected hardware limit from state_dim growth. Full 20-epoch run
    requires L40S/H100 CI verification.
  multi_fold_convergence smoke: not verified locally (same VRAM
    ceiling applies). L40S/H100 CI verification required.

The new slots follow the existing OFICalculator/MicrostructureState
pattern and consume signals already computed by ml-features — no new
crate, no ONNX, no stubs. All 12 sources were audited against their
implementation before persistence; every slot traces back to real
Mbp10Snapshot or MicrostructureState math.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 11:36:34 +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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