0c9d1ee39ece226fef02429d915a2445c44dc69b
VAL DIAGNOSTIC PROOF (train-4fpzx step=400):
pick=Long Full (target=0.66) prev_pos=0.0 → pos_post=0.0 actual_dir=Flat
trail=0, margin can't clip to 0 → only Kelly cap zeroed the target.
ROOT CAUSE:
effective_kelly = maturity * kelly_f + (1 - maturity) * warmup_floor
Cold-start fix (commit 2c97e0436) protected `warmup_floor` so it never
collapses to zero at maturity=0. But the warm branch was left exposed:
once maturity → 1 (>=10 completed trades), the blend collapses to
`kelly_f` alone, and `kelly_f = 0` is the natural state of
(payoff*win_rate - (1-win_rate)) / payoff
with balanced priors and small actual returns. Val environments with
pure per-bar P&L (no saboteur/shaping perturbations like training)
settle into this regime within ~10 trades — after which every non-Hold
target gets clamped to 0 deterministically. Identical bootstrap-deadlock
pattern to the IQN trunk SAXPY.
EVIDENCE:
val_picked_dir_dist [short=0.19 hold=0.20 long=0.39 flat=0.21] (kernel pick)
val_dir_dist [short=0.0001 hold=0.20 long=0.0000 flat=0.80] (post-physics)
100% of Long picks and ~99.95% of Short picks become actual_dir=Flat.
Hold passes through 1:1 (Hold skips margin/Kelly/trail in env_step).
VALDIAG step=400: act=77 (Long Full, target=0.66) prev=0.0 pos_post=0.0
-> confirms target zeroed before execute_trade; trail=0 rules out trail;
margin cap can't produce 0 with equity=$35K vs margin/contract=$17.9K.
FIX:
effective_kelly = max(kelly_f, warmup_floor)
The conviction-and-health-driven warmup_floor (in [0.5, 1.0]) becomes a
permanent minimum cap. `kelly_f` only takes over when the policy has
demonstrated enough edge to *exceed* the floor. Preserves design intent
(Kelly drives sizing once stats mature with real edge) while preventing
the bootstrap deadlock in environments where balanced trades naturally
yield kelly_f = 0.
All adaptive ISV-driven signals; no tuned constants.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%