ec972017ce
Research/validation-scope design for a coin-level capacity-, cost-, and leverage-honest
backtest reference, after quantifying (2026-07-15) that the book's numbers are tail-inflated:
top-10 days drive 58% of unlock / 29% of positioning; unlock's Sharpe collapses 1.03->0.19
under a P98 upside haircut; the "levered" backtest's -11.8% maxDD < the naive -15.4% (a
re-weighting artefact, not leverage).
Locked decisions (from brainstorming): coin-level ADV/impact model (turnover data verified:
818 coins, 2021-2026, USD); participation_cap 3%; AUM curve {35k,100k,350k,1M,10M} to locate
the ceiling; risk-parity/inverse-vol weighting; ex-ante risk layer with an anti-reactive gate
(G4) — reactive de-sizing stays out (A/B-rejected 3x); candidate edge #4 (pump/anomaly
detection) falsification-tested through the same honest-cost pipeline. No live cockpit change
(production gate-replacement is a follow-on). Self-critical section names the 5 ways this could
still fool us (recompute fidelity, slippage-is-modeled-not-measured, survivorship, AUM
relevance, still-a-backtest).
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.