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- Add NEWS to EventType enum and NewsEvent class to events.py
- Add insert_news_item, get_recent_news, upsert_symbol_score,
get_top_symbol_scores, upsert_market_sentiment,
get_latest_market_sentiment, insert_stock_selection,
get_stock_selections methods to Database class in db.py
- Add test_news_events.py and test_db_news.py with full coverage
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Add NewsCategory enum and NewsItem model to shared/models.py.
Create sentiment_models.py with SymbolScore, MarketSentiment, SelectedStock, Candidate.
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- Replace BTCUSDT/SOLUSDT/ETHUSDT with AAPL/MSFT in all test files
- Update backtester default symbol to AAPL
- Update strategy-engine default symbols to US stocks
- Update project description and CLI help text
- Remove empty superpowers docs directory
- Zero crypto references remaining in codebase
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- Replace Binance/ccxt with Alpaca REST client (paper + live)
- Add MOC (Market on Close) strategy for overnight gap trading
- Wire sentiment into strategy engine main loop
- Add EMA + bullish candle entry filters to Asian RSI
- Remove crypto-specific exchange factory
- Update config: Alpaca keys replace Binance keys
- 399 tests passing, lint clean
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- SentimentProvider: fetches Fear & Greed Index (free, no key),
CryptoPanic news sentiment (free key), CryptoQuant exchange
netflow (free key)
- SentimentData: aggregated should_buy/should_block logic
- Fear < 30 = buy opportunity, Greed > 80 = block buying
- Negative news < -0.5 = block buying
- Exchange outflow = bullish, inflow = bearish
- Integrated into Asian Session RSI strategy as entry filter
- All providers optional — disabled when API key missing
- 14 sentiment tests + 386 total tests passing
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- Technical indicators library (ATR, ADX, RSI, MACD, Bollinger, Stochastic, OBV)
- Signal model: conviction score, stop_loss, take_profit fields
- BaseStrategy: ADX regime filter, volume confirmation, ATR-based stops
- All 8 strategies upgraded with filters, conviction scoring, ATR stops
- Combined strategy uses conviction-weighted scoring
- 334 tests passing
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handling
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- Add 30 edge case tests (zero volume, empty data, extreme values,
strategy reset, notifier failures)
- Fix VWAP division by zero on zero-price candles
- Add DB transaction rollback on errors + transaction() context manager
- Add parameter validation to all 7 strategies with 41 validation tests
- Fix lint issues across test files
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- Fix ambiguous variable name in binance_rest.py
- Remove unused volumes variable in volume_profile_strategy.py
- Fix import ordering in backtester main.py and test_metrics.py
- Auto-format all files with ruff
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Replace raw asyncpg SQL with SQLAlchemy async engine, async_sessionmaker,
and ORM operations. Uses session.merge for candle upserts, session.add
for signal/order inserts, update() for status changes, select() for
queries. Auto-converts postgresql:// URLs to postgresql+asyncpg://.
Keeps init_tables() as backward-compatible alias for connect().
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Add SA 2.0 declarative models (CandleRow, SignalRow, OrderRow, TradeRow,
PositionRow, PortfolioSnapshotRow) mirroring existing asyncpg tables.
Set up Alembic with async PostgreSQL support and add migrate/migrate-down/
migrate-new Makefile targets. Update shared dependencies with sqlalchemy,
alembic, structlog, prometheus-client, pyyaml, aiohttp, and rich.
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Binance spot crypto trading platform with microservices architecture:
- shared: Pydantic models, Redis Streams broker, asyncpg DB layer
- data-collector: Binance WebSocket/REST market data collection
- strategy-engine: Plugin-based strategy execution (RSI, Grid)
- order-executor: Order execution with risk management
- portfolio-manager: Position tracking and PnL calculation
- backtester: Historical strategy testing with simulator
- cli: Click-based CLI for all operations
- Docker Compose orchestration with Redis and PostgreSQL
- 24 test files covering all modules
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