Market-data selection
Compare APIs, feeds, coverage, latency, licensing, asset classes and historical depth.
Market data APIs, alternative data and quant research infrastructure
Ledgerstone is a practical index of financial data sources, trading datasets and research infrastructure for builders, analysts and systematic investors.
Built for market-data evaluation, quant research, backtesting, data engineering and investment workflows.
Search by intent
Common financial-data queries
Start with the dataset or infrastructure question closest to your use case.
Market data APIs
Compare financial market data APIs by coverage, latency, history, licence and reliability.
Financial data APIs
Understand APIs for prices, fundamentals, filings, macro data, options, news and alternatives.
Historical market data
Evaluate historical prices, OHLCV, corporate actions and point-in-time backtesting needs.
Tick data
Understand trades, quotes, timestamp precision, storage and intraday research use cases.
Order book data
Learn how Level 2 data, bid-ask depth and liquidity feeds support microstructure research.
Alternative data providers
Compare web, jobs, app, geolocation, news, satellite and transaction-derived datasets.
Hedge fund data sources
Map the data categories used in market, fundamental, alternative and systematic research.
Quant research tools
Organise data, backtesting, feature generation, experiment tracking and production handoff.
Backtesting data
Check historical data quality, survivorship bias, lookahead bias and transaction-cost assumptions.
SEC filings data
Use filings, XBRL, identifiers, text extraction and event-detection workflows.
Economic data APIs
Compare macro indicators, release calendars, revisions and vintage-data requirements.
Options data APIs
Understand options chains, Greeks, implied volatility and historical options data.
Financial data work rarely fails because there is no data. It fails because the data is mis-specified, mispriced, misaligned with the strategy, difficult to licence, hard to normalise or too slow for the intended workflow.
Ledgerstone organises financial-data sources by query, resolution, use case and operational constraint.
Use cases
Built for serious data work
Quant research
Understand the data requirements behind signals, backtests, features and validation workflows.
Trading infrastructure
Separate batch research data, real-time feeds, order book data and low-latency production needs.
Data procurement
Evaluate source transparency, survivorship bias, corporate actions, redistribution rights and operational risk.
Data types
Where financial data work usually begins
| Category | Typical sources | Common use |
|---|---|---|
| OHLCV data | Market data APIs, exchange data, vendor feeds | Charts, screening, basic backtests |
| Tick data | Exchange feeds, specialist vendors | Intraday research, execution analysis, microstructure |
| Order book data | Level 2 feeds, crypto exchanges, specialist vendors | Market microstructure, liquidity, HFT research |
| Fundamental data | Filings, statements, vendor-normalised datasets | Equity research, factor models, screening |
| Alternative data | Web, app, card, geolocation, jobs, news, satellite | Signal discovery and differentiated research |
| Economic data | Central banks, statistical agencies, macro APIs | Macro analysis, rates, allocation models |
| Options data | OPRA-derived vendors, exchange feeds, specialist APIs | Volatility, Greeks, flow, derivatives research |
| News and text | News APIs, filings, transcripts, NLP pipelines | Event detection, sentiment, narrative analysis |
Guides
Initial data infrastructure guides
Market data APIA practical guide to market data APIs, including real-time feeds, historical prices, asset-class coverage, latency, licensing and integration checks.Financial data APIA practical guide to financial data APIs for prices, fundamentals, filings, macro data, options, news and alternative data workflows.Historical market dataA practical guide to historical market data, including OHLCV, tick data, corporate actions, survivorship bias and backtesting requirements.Tick dataA practical guide to tick data, including trades, quotes, timestamps, market microstructure, storage and research use cases.Order book dataA guide to order book data, including Level 2 market data, bid-ask depth, liquidity, exchange feeds and HFT research considerations.Alternative data providersA practical guide to alternative data providers, including web data, geolocation, app, jobs, news, satellite and transaction-derived datasets.Hedge fund data sourcesA practical guide to hedge fund data sources, including market data, fundamentals, filings, alternative data and research infrastructure.Quant research toolsA practical guide to quant research tools, including data sources, notebooks, feature stores, backtesting, experiment tracking and production handoff.Backtesting dataA practical guide to backtesting data, including historical prices, corporate actions, survivorship bias, point-in-time data and transaction costs.SEC filings dataA practical guide to SEC filings data, including company filings, APIs, XBRL, text extraction, event detection and research workflows.Economic data APIA guide to economic data APIs, including macro indicators, central bank data, statistical agencies, release calendars and revision caveats.Options data APIA practical guide to options data APIs, including options chains, Greeks, implied volatility, historical options data and licensing considerations.
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