feat: implement data-driven external data integration (issue #22)

Add objective external data sources to enhance trading decisions beyond
market prices and user input.

## New Modules

### src/data/news_api.py
- News sentiment analysis with Alpha Vantage and NewsAPI support
- Sentiment scoring (-1.0 to +1.0) per article and aggregated
- 5-minute caching to minimize API quota usage
- Graceful degradation when APIs unavailable

### src/data/economic_calendar.py
- Track major economic events (FOMC, GDP, CPI)
- Earnings calendar per stock
- Event proximity checking for high-volatility periods
- Hardcoded major events for 2026 (no API required)

### src/data/market_data.py
- Market sentiment indicators (Fear & Greed equivalent)
- Market breadth (advance/decline ratios)
- Sector performance tracking
- Fear/Greed score calculation

## Integration

Enhanced GeminiClient to seamlessly integrate external data:
- Optional news_api, economic_calendar, and market_data parameters
- Async build_prompt() includes external context when available
- Backward-compatible build_prompt_sync() for existing code
- Graceful fallback when external data unavailable

External data automatically added to AI prompts:
- News sentiment with top articles
- Upcoming high-impact economic events
- Market sentiment and breadth indicators

## Configuration

Added optional settings to config.py:
- NEWS_API_KEY: API key for news provider
- NEWS_API_PROVIDER: "alphavantage" or "newsapi"
- MARKET_DATA_API_KEY: API key for market data

## Testing

Comprehensive test suite with 38 tests:
- NewsAPI caching, sentiment parsing, API integration
- EconomicCalendar event filtering, earnings lookup
- MarketData sentiment and breadth calculations
- GeminiClient integration with external data sources
- All tests use mocks (no real API keys required)
- 81% coverage for src/data module (exceeds 80% requirement)

## Circular Import Fix

Fixed circular dependency between gemini_client.py and cache.py:
- Use TYPE_CHECKING for imports in cache.py
- String annotations for TradeDecision type hints

All 195 existing tests pass. No breaking changes to existing functionality.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

src/data/README.md

@@ -0,0 +1,205 @@
+# External Data Integration
+
+This module provides objective external data sources to enhance trading decisions beyond just market prices and user input.
+
+## Modules
+
+### `news_api.py` - News Sentiment Analysis
+
+Fetches real-time news for stocks with sentiment scoring.
+
+**Features:**
+- Alpha Vantage and NewsAPI.org support
+- Sentiment scoring (-1.0 to +1.0)
+- 5-minute caching to minimize API quota usage
+- Graceful fallback when API unavailable
+
+**Usage:**
+```python
+from src.data.news_api import NewsAPI
+
+# Initialize with API key
+news_api = NewsAPI(api_key="your_key", provider="alphavantage")
+
+# Fetch news sentiment
+sentiment = await news_api.get_news_sentiment("AAPL")
+if sentiment:
+    print(f"Average sentiment: {sentiment.avg_sentiment}")
+    for article in sentiment.articles[:3]:
+        print(f"{article.title} ({article.sentiment_score})")
+```
+
+### `economic_calendar.py` - Major Economic Events
+
+Tracks FOMC meetings, GDP releases, CPI, earnings calendars, and other market-moving events.
+
+**Features:**
+- High-impact event tracking (FOMC, GDP, CPI)
+- Earnings calendar per stock
+- Event proximity checking
+- Hardcoded major events for 2026 (no API required)
+
+**Usage:**
+```python
+from src.data.economic_calendar import EconomicCalendar
+
+calendar = EconomicCalendar()
+calendar.load_hardcoded_events()
+
+# Get upcoming high-impact events
+upcoming = calendar.get_upcoming_events(days_ahead=7, min_impact="HIGH")
+print(f"High-impact events: {upcoming.high_impact_count}")
+
+# Check if near earnings
+earnings_date = calendar.get_earnings_date("AAPL")
+if earnings_date:
+    print(f"Next earnings: {earnings_date}")
+
+# Check for high volatility period
+if calendar.is_high_volatility_period(hours_ahead=24):
+    print("High-impact event imminent!")
+```
+
+### `market_data.py` - Market Indicators
+
+Provides market breadth, sector performance, and sentiment indicators.
+
+**Features:**
+- Market sentiment levels (Fear & Greed equivalent)
+- Market breadth (advancing/declining stocks)
+- Sector performance tracking
+- Fear/Greed score calculation
+
+**Usage:**
+```python
+from src.data.market_data import MarketData
+
+market_data = MarketData(api_key="your_key")
+
+# Get market sentiment
+sentiment = market_data.get_market_sentiment()
+print(f"Market sentiment: {sentiment.name}")
+
+# Get full indicators
+indicators = market_data.get_market_indicators("US")
+print(f"Sentiment: {indicators.sentiment.name}")
+print(f"A/D Ratio: {indicators.breadth.advance_decline_ratio}")
+```
+
+## Integration with GeminiClient
+
+The external data sources are seamlessly integrated into the AI decision engine:
+
+```python
+from src.brain.gemini_client import GeminiClient
+from src.data.news_api import NewsAPI
+from src.data.economic_calendar import EconomicCalendar
+from src.data.market_data import MarketData
+from src.config import Settings
+
+settings = Settings()
+
+# Initialize data sources
+news_api = NewsAPI(api_key=settings.NEWS_API_KEY, provider=settings.NEWS_API_PROVIDER)
+calendar = EconomicCalendar()
+calendar.load_hardcoded_events()
+market_data = MarketData(api_key=settings.MARKET_DATA_API_KEY)
+
+# Create enhanced client
+client = GeminiClient(
+    settings,
+    news_api=news_api,
+    economic_calendar=calendar,
+    market_data=market_data
+)
+
+# Make decision with external context
+market_data_dict = {
+    "stock_code": "AAPL",
+    "current_price": 180.0,
+    "market_name": "US stock market"
+}
+
+decision = await client.decide(market_data_dict)
+```
+
+The external data is automatically included in the prompt sent to Gemini:
+
+```
+Market: US stock market
+Stock Code: AAPL
+Current Price: 180.0
+
+EXTERNAL DATA:
+News Sentiment: 0.85 (from 10 articles)
+  1. [Reuters] Apple hits record high (sentiment: 0.92)
+  2. [Bloomberg] Strong iPhone sales (sentiment: 0.78)
+  3. [CNBC] Tech sector rallying (sentiment: 0.85)
+
+Upcoming High-Impact Events: 2 in next 7 days
+  Next: FOMC Meeting (FOMC) on 2026-03-18
+  Earnings: AAPL on 2026-02-10
+
+Market Sentiment: GREED
+Advance/Decline Ratio: 2.35
+```
+
+## Configuration
+
+Add these to your `.env` file:
+
+```bash
+# External Data APIs (optional)
+NEWS_API_KEY=your_alpha_vantage_key
+NEWS_API_PROVIDER=alphavantage  # or "newsapi"
+MARKET_DATA_API_KEY=your_market_data_key
+```
+
+## API Recommendations
+
+### Alpha Vantage (News)
+- **Free tier:** 5 calls/min, 500 calls/day
+- **Pros:** Provides sentiment scores, no credit card required
+- **URL:** https://www.alphavantage.co/
+
+### NewsAPI.org
+- **Free tier:** 100 requests/day
+- **Pros:** Large news coverage, easy to use
+- **Cons:** No sentiment scores (we use keyword heuristics)
+- **URL:** https://newsapi.org/
+
+## Caching Strategy
+
+To minimize API quota usage:
+
+1. **News:** 5-minute TTL cache per stock
+2. **Economic Calendar:** Loaded once at startup (hardcoded events)
+3. **Market Data:** Fetched per decision (lightweight)
+
+## Graceful Degradation
+
+The system works gracefully without external data:
+
+- If no API keys provided → decisions work with just market prices
+- If API fails → decision continues without external context
+- If cache expired → attempts refetch, falls back to no data
+- Errors are logged but never block trading decisions
+
+## Testing
+
+All modules have comprehensive test coverage (81%+):
+
+```bash
+pytest tests/test_data_integration.py -v --cov=src/data
+```
+
+Tests use mocks to avoid requiring real API keys.
+
+## Future Enhancements
+
+- Twitter/X sentiment analysis
+- Reddit WallStreetBets sentiment
+- Options flow data
+- Insider trading activity
+- Analyst upgrades/downgrades
+- Real-time economic data APIs