jgrusewski d1638959d3 fix(sp21): Return v3.1 — drop short-rollout guard for volume bars (atomic)
Single-file fix to `compute_epoch_financials`: remove the
`if n_returns_f >= bars_per_year` short-rollout fallback that
left v2 semantics in place for sub-year rollouts. For Foxhunt's
volume bars, `bars_per_day ≈ 34_496` → `bars_per_year ≈ 8.69M`,
while a training epoch produces `n_returns ≈ 4.10M`. The guard
fired on every production epoch, so the v3 CAGR fix was a no-op.

Diagnosis chain:
- v3 commit (2937da889) merged the n_returns >= bars_per_year guard
- Smoke v4 (commit 62b5a50e8, workflow train-frv8x) epoch 1 showed
  Return=+2.963e2% — bit-identical to v1's pre-fix output
- Hypothesis 1 (cache poisoning): ruled out — ensure-binary log
  shows "Cache MISS: compiling binaries for 62b5a50e8" and ml crate
  was recompiled fresh
- Hypothesis 2 (different commit): ruled out — workflow params confirm
  commit-sha = 62b5a50e8 = current HEAD
- Hypothesis 3 (bars_per_year mismatch): confirmed — v4 log emits
  "Bars per day (from data): 34496" which makes bars_per_year > n_returns
  and triggers the v2 fallback inside the v3 branch

Fix: unconditional CAGR. The log-space clamp [-23, +20] bounds
the display in all edge cases (tests with tiny n_returns
extrapolate aggressively; the clamp caps at exp(20) - 1 ≈ +4.85e8%).

Expected v5 epoch 1 Return: ~+1.770e3% (was +2.963e2% under v4).
The new value is the *actual annualized* projection: 1377% over
a 0.47-year rollout. Overfit cycles cap at +4.85e8% (was +e19%).

Tests:
- cargo test -p ml --lib financials → 7/7
- Sign-only assertions in test cases (all > 0.0) — no regressions

Files changed:
- crates/ml/src/trainers/dqn/financials.rs: 1 conditional removed,
  comment block updated with v3 → v3.1 history
- docs/dqn-wire-up-audit.md: diagnosis + fix entry for 2026-05-11

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 09:12:56 +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
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Python 1.3%
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