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.