jgrusewski 22e6ddbcac fix(rl): eval_summary aggregates across all b_size accounts (E.4-E.5)
Replaces the broken single-account + scale-mismatch slicing block in
alpha_rl_train.rs eval phase with proper per-account aggregation.

Pre-fix (cluster v11 alpha-rl-8ll7j, b=1024):
  head_before_eval = sim.read_total_trade_count()  // aggregate=1,203,376
  all_records      = sim.read_trade_records(0)     // backtest 0 only, ≤1024
  // 1.2M > 1024 → wrap branch fires → eval_records = ALL 1024 records
  //   from account 0, mixing train+eval trades
  eval_summary: n_trades=1024 pnl=$61,513 wr=0.217 — MEANINGLESS

Post-fix (this commit, b=16 local smoke):
  head_before_per_b = sim.read_per_backtest_trade_counts()
  all_per_b         = sim.read_trade_records_all()
  // for each backtest: slice ring by per-account head_before vs head_after,
  //   handle wrap correctly, aggregate eval-only records
  eval_summary: n_trades=226 pnl=$-41,137 wr=0.376
  n_eval_trades_seen=226 (= captured) n_dropped=0 n_pre_eval_wrapped=0

Local smoke validation (b=16, 1k train + 250 eval, fold 1 ES.FUT all):
  - n_trades jumped 58 → 226 (4× — confirms aggregation across 16 accts)
  - per-account pre-eval heads: min=16 max=59 sum=596 (correct scale)
  - n_eval_trades_seen == n_trades (no wrap at this scale)
  - eval_summary.json gained 4 new fields:
      n_eval_trades_seen, n_eval_trades_dropped,
      n_pre_eval_trades_wrapped, b_size

Existing keys (n_trades, total_pnl_usd, profit_factor, sharpe_ann,
max_drawdown_usd, win_rate) preserved for downstream G8-gate / Argo
aggregator consumers (per spec §3).

Cluster validation pending Phase A cluster (alpha-rl-jz48s) completion
to avoid alpha_rl_train.rs branch conflict. After Phase A merges,
this fix can submit alongside.

Spec: docs/superpowers/specs/2026-05-31-eval-summary-trade-aggregation-design.md
Plan: docs/superpowers/plans/2026-05-31-eval-summary-trade-aggregation.md

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-31 18:09:16 +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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