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name: data-vendors
Provides Ktor server patterns for routing DSL, plugins (auth, CORS, serialization), Koin DI, WebSockets, services, and testApplication testing.
Conducts multi-source web research with firecrawl and exa MCPs: searches, scrapes pages, synthesizes cited reports. For deep dives, competitive analysis, tech evaluations, or due diligence.
Provides demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation for multi-location retailers managing 300-800 SKUs.
name: data-vendors description: Financial data vendors — Bloomberg, Refinitiv, Polygon, Alpha Vantage. origin: ECT
Vendor | Coverage | Frequency | Cost | API Quality | Best For
----------------|-------------|------------|----------------|-------------|------------------
Bloomberg | Global, all | Tick-daily | $24K+/yr term | Excellent | Institutional, research
Refinitiv/LSEG | Global, all | Tick-daily | $15K+/yr | Good | Enterprise, FX/rates
Polygon.io | US equities | Tick-daily | $29-$199/mo | Excellent | US equity/options algo
Alpha Vantage | US+global | Min-daily | Free-$50/mo | Basic | Learning, prototyping
Yahoo Finance | Global | Daily | Free | Unofficial | Screening, basic research
IEX Cloud | US equities | Daily | $9-$500/mo | Good | US equities, affordable
Nasdaq Data Link| Mixed | Daily | Free-$500/mo | Good | Quant research, alt data
EODHD | Global | Daily | $20-$80/mo | Decent | Global equities on budget
Tiingo | US equities | Daily-IEX | Free-$30/mo | Good | Hobbyist, basic needs
Databento | US futures | Tick | Usage-based | Excellent | Futures algo trading
Norgate | US+global | Daily | $50-$150/mo | File-based | Backtesting (survivorship-free)
WRDS | Academic | Mixed | Academic license| Database | Academic research
Bloomberg Professional (Terminal):
- Cost: ~$24,000/year per seat
- Coverage: most comprehensive — equities, fixed income, commodities, FX, derivatives, economics
- Unique data: consensus estimates (BEst), credit ratings, corporate actions, supply chain
- Bloomberg Data License (BDL): enterprise feed for systematic strategies
- BLPAPI: programmatic access via Python, Java, C++
Key Bloomberg data fields:
PX_LAST: Last price
PX_OPEN/HIGH/LOW/CLOSE: OHLC data
VOLUME: Trading volume
BEST_EPS: Consensus EPS estimate
CUR_MKT_CAP: Market capitalization
TRAIL_12M_EPS: Trailing 12-month EPS
DVD_YIELD: Dividend yield
PX_TO_BOOK_RATIO: Price-to-book
TOT_RETURN_INDEX_GROSS_DVDS: Total return index (includes dividends)
Bloomberg advantages:
- Point-in-time fundamental data (BEST estimates are timestamped)
- Corporate action adjustments built in
- Survivorship-bias-free equity universe histories
- Global coverage including EM, fixed income, derivatives
- Reference data: sector classification, index membership history
Bloomberg limitations:
- Expensive ($24K/seat minimum)
- Data redistribution restrictions (licensing)
- API has learning curve (BLPAPI, BQL)
- Not ideal for high-frequency tick data (use dedicated feeds instead)
Refinitiv (now part of London Stock Exchange Group):
- Formerly Thomson Reuters financial data
- Eikon terminal: ~$15K-22K/year
- Refinitiv Data Platform: cloud-based API access
- Tick History: comprehensive tick data archive (decades of history)
Key products:
Eikon / Workspace: terminal for research and trading
Refinitiv Data Platform API: REST/WebSocket for programmatic access
DataScope: bulk data delivery for quantitative research
Tick History: institutional-grade tick data (25+ years)
StarMine: quantitative analytics (analyst revision models, intrinsic value)
I/B/E/S: consensus estimates (industry standard for academic research)
Refinitiv advantages:
- Strong in FX and fixed income data
- I/B/E/S estimates are the academic standard
- Tick History is comprehensive for backtesting microstructure
- ESG data (one of the largest ESG datasets)
- Good for global coverage, especially non-US markets
Refinitiv limitations:
- Pricing complex and opaque
- API migration from legacy (Eikon) to new platform ongoing
- Data quality varies by market and asset class
- Less community/open-source support than Bloomberg
Polygon.io:
- Focus: US equities, options, forex, crypto
- Plans: Starter ($29/mo), Developer ($79/mo), Advanced ($199/mo), Enterprise
- REST API + WebSocket for real-time streaming
- Historical data: tick-level for equities and options
Key features:
- Aggregated bars: 1-min to daily OHLCV
- Tick-level data: individual trades and quotes
- Options data: all listed US options (quotes, trades, Greeks)
- Reference data: tickers, exchanges, dividends, splits
- Flat files: bulk download for backtesting
API patterns:
REST: /v2/aggs/ticker/{ticker}/range/{multiplier}/{timespan}/{from}/{to}
WebSocket: wss://socket.polygon.io/stocks (real-time trades, quotes)
Rate limits: varies by plan (unlimited on Advanced+)
Polygon advantages:
- Clean REST API with good documentation
- Affordable tick data (vs $50K+ for institutional tick feeds)
- Options data included (unusual at this price point)
- Good for algorithmic trading development
- Flat file access for bulk historical analysis
Polygon limitations:
- US-only coverage (no international equities)
- No fundamental data (no earnings, financial statements)
- Data quality: occasional gaps, delayed corrections
- No point-in-time fundamental data
Alpha Vantage:
- Free tier: 25 API calls/day
- Premium: $50/month for 75 calls/minute
- Coverage: US + global equities, FX, crypto, economic indicators
Key endpoints:
TIME_SERIES_DAILY: daily OHLCV
TIME_SERIES_INTRADAY: 1-min to 60-min bars
GLOBAL_QUOTE: latest price snapshot
OVERVIEW: company fundamentals (balance sheet, income statement)
EARNINGS: quarterly EPS data
ECONOMIC indicators: GDP, CPI, interest rates
Alpha Vantage advantages:
- Free tier available (good for learning and prototyping)
- Simple API with JSON/CSV output
- Includes basic fundamental data
- Technical indicators built in (SMA, EMA, RSI, MACD)
Alpha Vantage limitations:
- Aggressive rate limiting (25 calls/day on free tier)
- Data quality issues (gaps, delayed corporate action adjustments)
- No tick data
- Limited historical depth for some series
- Not suitable for production systematic trading
End-of-day (EOD) price data:
Fields: date, open, high, low, close, volume, adjusted_close
Adjusted close: accounts for splits and dividends
Quality range: high (Bloomberg, Norgate) to variable (free sources)
Key issue: adjustment methodology differs across vendors
Intraday / tick data:
Fields: timestamp, price, size, exchange, conditions
Timestamp resolution: microseconds (exchanges) to seconds (aggregators)
Data volume: ~1-2 GB/day for all US equities (trades only)
Quality: exchange direct feeds are best; aggregators may miss trades
Fundamental data:
Fields: financial statement items, ratios, estimates
Frequency: quarterly (10-Q), annual (10-K), as-reported vs restated
Key issue: point-in-time availability (when was data first available?)
Quality: Bloomberg/Refinitiv best; free sources often have look-ahead bias
Reference data:
Fields: ticker, CUSIP, ISIN, SEDOL, exchange, sector, index membership
Key issue: identifier changes over time (ticker changes, mergers)
Critical: index constituent history (for survivorship-free backtesting)
Corporate actions:
Types: splits, dividends, spin-offs, mergers, ticker changes
Key issue: adjustment factors must be applied correctly
Vendor differences: adjustment methodology varies (total return vs price return)
Best practices for data ingestion:
1. Rate limiting:
- Respect vendor rate limits (implement exponential backoff)
- Cache responses locally (don't re-fetch unchanged data)
- Use bulk/batch endpoints when available
2. Data storage:
- Store raw vendor responses (immutable archive)
- Build processed/clean layer on top
- Timestamp each data point with retrieval time (point-in-time)
3. Error handling:
- Validate response schema (fields present, types correct)
- Handle partial data (some fields missing)
- Log and alert on data quality anomalies
- Retry with exponential backoff on transient errors
4. Corporate action handling:
- Subscribe to corporate action feed (or poll daily)
- Apply adjustments to historical data retroactively
- Maintain both adjusted and unadjusted price series
- Test: total return calculation should match vendor's total return index
5. Multi-vendor reconciliation:
- Cross-check prices across vendors (flag discrepancies > 1%)
- Use one vendor as primary, another as validation
- Especially important for: corporate actions, delisted securities, thin markets
Budget-conscious data architecture:
Tier 1 — Free/cheap (prototyping and learning):
Price data: Yahoo Finance (unofficial API), Alpha Vantage free tier
Fundamentals: SEC EDGAR (XBRL filings), Alpha Vantage
Economic: FRED (Federal Reserve Economic Data)
Cost: $0-50/month
Tier 2 — Serious hobbyist / small fund:
Price data: Polygon.io ($79-199/month) or Tiingo ($30/month)
Fundamentals: SimFin, Financial Modeling Prep ($30-100/month)
Alternative: Nasdaq Data Link free datasets, Google Trends
Cost: $150-400/month
Tier 3 — Professional / small hedge fund:
Price data: Polygon.io Advanced + Norgate for clean historical
Fundamentals: S&P Capital IQ or FactSet ($5-15K/year)
Tick data: Databento or Polygon flat files
Alternative: selected alt data vendor ($50-200K/year)
Cost: $2-20K/month
Tier 4 — Institutional:
Bloomberg Data License or Refinitiv DataScope
Multiple alt data vendors
Direct exchange feeds for latency-sensitive
Cost: $50K+/month
Before relying on a data vendor for trading: