jgrusewski 336ee40b9d spec(dqn): add Invariant 9 — no deferred work, no stubs, concrete E decisions
User-mandated addition:

Invariant 9 — No deferred work, no stubs, no TODO/FIXME
Every commit lands complete. No stubs (placeholder return values), no
TODO/FIXME/XXX/HACK/TBD markers, no half-finished implementations. If
it can't finish in this commit, it doesn't start. Stubs and deferrals
train the network on semantic emptiness — invisible in convergence
metrics but burn GPU time optimising against partly-fake signal.
Authority: feedback_no_stubs.md, feedback_no_todo_fixme.md,
feedback_no_quickfixes.md elevated to first-class spec enforcement.
Pre-commit hook greps for forbidden markers.

Part E decisions made concrete (per Invariant 9):
- E.1 TFT VSN: IN (full VSN extension)
- E.2 GRN: IN if A.5 audit finds absent (otherwise mark existing as canonical)
- E.3 Multi-quantile heads: IN (5/25/50/75/95 quantile decomposition)
- E.4 Encoder-decoder: IN (extends D.3 to full trunk/head separation)
- E.5 Interpretability: IN (attention-weight ISV diagnostics)
- E.6 Auxiliary heads: IN (next-return + regime-classification)
- xLSTM: OUT (redundant with Mamba2+TLOB; YAGNI)
- KAN: OUT (function approx not a bottleneck)
No "evaluate later" items. Every concept either lands or explicitly
doesn't, with rationale.

§8 decisions tightened:
- D.8 TLOB mode: decision criterion = per-step cost benchmark ≤ 5ms
- C.6 controller order: fixed in spec (atoms→gamma→Kelly→cql_alpha→
  tau→epsilon→conviction_floor→plan_threshold→balancer)
- A.3 resource plan: auto-switch L40S→H100 at 12 GPU-hour threshold
- A.4 metric band init: [mean − 3σ, mean + 3σ] from last 3 good runs

No discretionary "we'll see" remain. All decisions data/order/budget/
statistic-driven.

Counter updates: "seven invariants" → "nine" in §3 header and §5
cleanup contract.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 09:32:22 +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
No description provided
Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
PLpgSQL 0.8%
Other 0.8%