jgrusewski 235961987d plan(crt-a): Phase A continuous controller implementation plan
Per docs/superpowers/specs/2026-05-20-continuous-reasoning-trader-design.md
(v2, commit 8ba8755b4). One plan per phase per writing-plans guidance —
Phase B/C/D plans written after each prior gate closes.

Phase A scope:
  A0 - Investigate forward_only cost model (read-only research,
       writes memo to docs/superpowers/memos/). STOP condition if
       trunk forward is stateless K-window per call (Case 2) —
       requires user approval to expand scope.
  A1 - Atomic delete of decision_stride (greenfields, no compat).
       Removes from SweepBase, ResolvedSimVariant, BatchedSimConfig,
       BacktestHarness, all YAMLs.
  A2 - Minimal Wiener-α conviction-EMA smoothing in decision_policy_*
       kernels. Three new device slots: conviction_ema_d,
       conviction_diff_var_ema_d, conviction_sample_var_ema_d. Floor
       at 0.4 per pearl_wiener_alpha_floor_for_nonstationary.
       First-observation bootstrap. Direction stays from raw alpha;
       magnitude/sizing uses smoothed value.
  A3 - Local compile + tests.
  A4 - Cluster smoke + Gate 1 validation against spec §3.6 acceptance.
       Memory entry on closure (green/red/yellow).
  A5 - Conditional hyperactivity mitigation (raise floor 0.4→0.6 OR
       add target-delta hysteresis). Fires only if Gate 1 reveals
       trade-count balloon.

Out of scope (deferred): full §4.4 multi-horizon conviction formula,
§4.3 conviction-degradation exit, §5 envelope, §6 LoRA adapter, §7
open_trade_state expansion — all Phase B/C/D.

Pearl conformance:
  - feedback_no_partial_refactor (atomic delete)
  - feedback_no_legacy_aliases (no compat shim)
  - feedback_push_before_deploy
  - pearl_wiener_optimal_adaptive_alpha
  - pearl_wiener_alpha_floor_for_nonstationary
  - pearl_first_observation_bootstrap
  - feedback_stop_on_anomaly (Gate 1 RED → diagnose, don't advance)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-20 17:33:16 +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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Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
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