33 lines
1.7 KiB
Markdown
33 lines
1.7 KiB
Markdown
# Backtest Strategy ICM Workspace
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This workspace orchestrates rules-based strategy backtesting for the operator's core
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styles (SPY 0DTE credit spreads, single-leg equity/options day trades) using TTG data
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servers as the only market-data source and a local pure-Python engine.
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The agent follows the numbered stages to freeze strategy rules, verify data depth,
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build the data cache, run the backtest, and produce an honest report.
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Folder structure:
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- CLAUDE.md (Layer 0): workspace identity
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- CONTEXT.md (Layer 1): workspace-level routing
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- stages/: numbered stage folders
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- 00_clarify_strategy/: freeze rules into a spec (with operator)
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- 01_verify_data/: enumerate contracts + verify historical depth
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- 02_fetch_cache/: pull bars/quotes into the shared cache
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- 03_run_backtest/: run the engine over cached data
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- 04_report/: render findings with small-sample honesty
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- _config/: Layer 3 reference material (stable across runs)
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- shared/: data cache (SQLite) + engine scripts
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- Each stage's output/ holds Layer 4 working artifacts for handoff to next stage.
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## Hard rules (apply to every stage)
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- Market data comes ONLY from TTG data servers. Never scrape or substitute public sites.
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- Python is stdlib-only. NO package installs. The operator manages packaging with uv
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(pyproject.toml in the workspace root has zero dependencies by design).
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- No look-ahead: a signal on bar N may only use bars <= N.
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- Every stage ends at a review gate. output/ is read (and optionally edited by the
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operator) before the next stage runs.
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- Clear a stage's output/ before re-running it.
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- Backtest results are research, not trade plans. Any live trade still goes through
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the normal cockpit path.
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