9e3040be04
Ex-ante sleeve-level volatility-target overlay on crypto_tstrend (TrendRunner): scale exposure DOWN in high-realized-vol regimes, never lever (cap=1.0). OOS investigation (881 test days) shows +0.24 book Sharpe / -1.4pp maxDD, robust net-of-cost to 40bp/turn and across L/floor params. Distinguished from the 3x rejected reactive de-sizing (conditions on vol, not drawdown; improves DD). Strict gates: net-book re-measure >=0.2 Sharpe, anti-pro-cyclical falsification, per-year consistency. Shadow-first deploy (false-WAIT-safe). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
fxhnt
Agentic strategy-research & multi-strategy execution platform. It systematically discovers, backtests and out-of-sample-validates trading strategies across many markets, keeps only what survives a rigorous statistical gauntlet, and runs the survivors live (multiple strategies at once).
The bet is not a secret edge — it's breadth + discipline + automation. The hard part (and the moat) is refusing to fool yourself at scale; the validation gauntlet is the core, built and proven first.
Architecture (hexagonal / ports-and-adapters)
src/fxhnt/
domain/ pure logic: gauntlet (Deflated Sharpe), strategies, backtest, models ← no I/O
ports/ contracts: DataProvider, repositories (the only seams)
adapters/ infra: yahoo data, SQLAlchemy (Postgres/SQLite) + DuckDB stores
application/ use-case services (ResearchService) — orchestrate via ports
cli.py composition root (wires concrete adapters)
See docs/architecture/0001-architecture.md.
Quickstart
pip install -e ".[dev]"
pytest # unit (gauntlet falsification) + integration (vertical slice)
fxhnt strategies # list strategy kinds
fxhnt research SPY --kind trend --window 200 # data → backtest → gauntlet → persist
fxhnt list --passed-only # the survivor library
Config via FXHNT_* env vars (e.g. FXHNT_OPERATIONAL_DSN=postgresql+psycopg://...). Defaults to
SQLite + a local DuckDB file under ~/.fxhnt/.
Status
Vertical slice working: data (Yahoo) → strategy (trend) → backtest (net of costs) → IS/OOS gauntlet → persistence (operational + analytical). Next: the multi-strategy execution layer, more strategy templates + data adapters, and the agentic discovery search on top of the proven gauntlet.