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docs: update README, runbook, and steering files for today's changes

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- README: added AI agent management section, updated paper trading
  description (no manual capital controls, broker-synced reset)
- Steering: migration numbers updated to 027 (next: 028), added
  trading engine endpoint, ruff pinning and isort config notes
- Runbook: already had reset/Alpaca sections from earlier commits
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Celes Renata
2026-04-17 04:37:44 +00:00
parent fde819ec09
commit 0f06cf8971
3 changed files with 14 additions and 4 deletions
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README.md
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@@ -77,6 +77,9 @@ Seed data: `python -m services.symbol_registry.seed`
### Autonomous Trading Engine
Continuous decision loop that polls for actionable recommendations and executes paper trades without manual intervention. Includes confidence-based position sizing (with sample-size-dampened agreement scoring to prevent thin-evidence inflation), dynamic stop-loss/take-profit (ATR-based), circuit breakers (daily loss cap, single-position loss, volatility detection), reserve pool management (auto-siphon from profits), risk tier auto-adjustment (conservative/moderate/aggressive based on trailing performance), portfolio rebalancing (sector and concentration limits), gradual entry (multi-tranche orders), correlation-aware diversification, earnings calendar awareness, portfolio heat management, tax-lot tracking with wash sale detection, performance tracking (Sharpe, drawdown, win rate, profit factor), and backtesting against historical data.
### AI Agent Management
Configurable AI agents (document extractor, event classifier, thesis rewriter) with database-driven model/prompt resolution. 60-second TTL cache for hot-swapping models without restarts. Agent performance logging with variant attribution for future A/B testing support.
### Global News Interpolation
Macro/geopolitical event ingestion from dedicated sources. Ollama-based classification by impact type, severity, affected regions, and sectors. Company exposure profiles (geographic revenue mix, supply chain regions, commodity dependencies, market position tier) map events to per-company macro impact scores with resilience modifiers. Forward-looking trend projections combine company momentum with macro trajectories.
@@ -105,7 +108,8 @@ Historical pattern mining on the platform's own data — how similar catalyst ty
### Paper Trading
- Alpaca paper trading integration (3 accounts max per Alpaca owner)
- Full reset: liquidates broker positions, cancels orders, syncs capital from broker balance
- Full reset: liquidates broker positions, cancels orders, clears local DB, syncs capital from broker's actual account balance
- No manual capital controls — engine capital always derived from broker state on reset
- Moderate risk tier default, auto-adjustable
- Full execution audit trail from signal to broker response
- Operator approval workflow available for live mode