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feature/issue-20-volatility-hunter
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8 Commits

Author SHA1 Message Date
agentson
62b1a1f37a feat: implement Volatility Hunter for real-time market scanning
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Details 
Implements issue #20 - Behavioral Rule: Volatility Hunter

Components:
1. src/analysis/volatility.py
   - VolatilityAnalyzer with ATR calculation
   - Price change tracking (1m, 5m, 15m intervals)
   - Volume surge detection (ratio vs average)
   - Price-volume divergence analysis
   - Momentum scoring (0-100 scale)
   - Breakout/breakdown detection

2. src/analysis/scanner.py
   - MarketScanner for real-time stock scanning
   - Scans all available stocks every 60 seconds
   - Ranks by momentum score
   - Identifies top 5 movers per market
   - Dynamic watchlist updates

3. Integration with src/main.py
   - Auto-adjust WATCHLISTS dynamically
   - Replace laggards with leaders (max 2 per scan)
   - Volume confirmation required
   - Integrated with Context Tree L7 (real-time layer)

4. Comprehensive tests
   - 22 tests in tests/test_volatility.py
   - 99% coverage for analysis module
   - Tests for all volatility calculations
   - Tests for scanner ranking and watchlist updates
   - All tests passing

Key Features:
- Scan ALL stocks, not just current watchlist
- Dynamic watchlist that adapts to market leaders
- Context Tree integration for real-time data storage
- Breakout detection with volume confirmation
- Multi-timeframe momentum analysis

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-04 16:29:06 +09:00
agentson
2f9efdad64 feat: integrate decision logger with main trading loop
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- Add DecisionLogger to main.py trading cycle
- Log all decisions with context snapshot (L1-L2 layers)
- Capture market data and balance info in context
- Add comprehensive tests (9 tests, 100% coverage)
- All tests passing (63 total)

Implements issue #17 acceptance criteria:
- ✅ decision_logs table with proper schema
- ✅ DecisionLogger class with all required methods
- ✅ Automatic logging in trading loop
- ✅ Tests achieve 100% coverage of decision_logger.py
- ⚠️  Context snapshot uses L1-L2 data (L3-L7 pending issue #15)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-04 15:47:53 +09:00
agentson
6551d7af79 WIP: Add decision logging infrastructure 
- Add decision_logs table to database schema
- Create decision logger module with comprehensive logging
- Prepare for decision tracking and audit trail

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-04 15:47:53 +09:00
agentson
917b68eb81 feat: implement L1-L7 context tree for multi-layered memory management
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Details 
Implements Pillar 2 (Multi-layered Context Management) with a 7-tier
hierarchical memory system from real-time market data to generational
trading wisdom.

## New Modules
- `src/context/layer.py`: ContextLayer enum and metadata config
- `src/context/store.py`: ContextStore for CRUD operations
- `src/context/aggregator.py`: Bottom-up aggregation (L7→L6→...→L1)

## Database Changes
- Added `contexts` table for hierarchical data storage
- Added `context_metadata` table for layer configuration
- Indexed by layer, timeframe, and updated_at for fast queries

## Context Layers
- L1 (Legacy): Cumulative wisdom (kept forever)
- L2 (Annual): Yearly metrics (10 years retention)
- L3 (Quarterly): Strategy pivots (3 years)
- L4 (Monthly): Portfolio rebalancing (2 years)
- L5 (Weekly): Stock selection (1 year)
- L6 (Daily): Trade logs (90 days)
- L7 (Real-time): Live market data (7 days)

## Tests
- 18 new tests in `tests/test_context.py`
- 100% coverage on context modules
- All 72 tests passing (54 existing + 18 new)

## Documentation
- Added `docs/context-tree.md` with comprehensive guide
- Updated `CLAUDE.md` architecture section
- Includes usage examples and best practices

Closes #15

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-04 14:12:29 +09:00
agentson
b26ff0c1b8 feat: implement timezone-based global market auto-selection
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Details 
Implement comprehensive multi-market trading system with automatic
market selection based on timezone and trading hours.

## New Features
- Market schedule module with 10 global markets (KR, US, JP, HK, CN, VN)
- Overseas broker for KIS API international stock trading
- Automatic market detection based on current time and timezone
- Next market open waiting logic when all markets closed
- ConnectionError retry with exponential backoff (max 3 attempts)

## Architecture Changes
- Market-aware trading cycle with domestic/overseas broker routing
- Market context in AI prompts for better decision making
- Database schema extended with market and exchange_code columns
- Config setting ENABLED_MARKETS for market selection

## Testing
- 19 new tests for market schedule (timezone, DST, lunch breaks)
- All 54 tests passing
- Lint fixes with ruff

## Files Added
- src/markets/schedule.py - Market schedule and timezone logic
- src/broker/overseas.py - KIS overseas stock API client
- tests/test_market_schedule.py - Market schedule test suite

## Files Modified
- src/main.py - Multi-market main loop with retry logic
- src/config.py - ENABLED_MARKETS setting
- src/db.py - market/exchange_code columns with migration
- src/brain/gemini_client.py - Dynamic market context in prompts

Resolves #5

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-04 09:29:25 +09:00
Jiho Son
006aaed46a Fix SSL hostname mismatch for KIS VTS paper trading endpoint
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Details 
The KIS virtual trading server (openapivts.koreainvestment.com) serves a
certificate with a hostname mismatch. Disable SSL hostname verification
only for the VTS endpoint via a custom TCPConnector; production endpoints
remain fully verified.

Closes #1

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-02-04 03:10:32 +09:00
Jiho Son
e025136047 Fix Docker runtime errors: migrate to google-genai SDK and fix SQLite permissions
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Details 
Migrate from deprecated google-generativeai to google-genai (>=1.0) using the
new Client-based API, and fix SQLite "unable to open database file" in Docker
by chowning the data directory to appuser before switching users.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-02-04 02:56:31 +09:00
Jiho Son
d1750af80f Add complete Ouroboros trading system with TDD test suite
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Details 
Implement the full autonomous trading agent architecture:
- KIS broker with async API, token refresh, leaky bucket rate limiter, and hash key signing
- Gemini-powered decision engine with JSON parsing and confidence threshold enforcement
- Risk manager with circuit breaker (-3% P&L) and fat finger protection (30% cap)
- Evolution engine for self-improving strategy generation via failure analysis
- 35 passing tests written TDD-first covering risk, broker, and brain modules
- CI/CD pipeline, Docker multi-stage build, and AI agent context docs

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-02-04 02:08:48 +09:00