> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/finance-and-accounting/coin-api/data-overview.md). # Data Overview Coin API gives you access to three types of historical cryptocurrency market data. Each entity focuses on a different level of market detail — from aggregated candles to tick-level trades and quotes. ## Entities | Entity | Best for | | ---------------------- | ------------------------------------------------------------- | | OHLCV Historical Data | Price trend analysis, charting, backtesting strategies | | Trades Historical Data | Execution analysis, volume profiling, microstructure research | | Quotes Historical Data | Spread analysis, liquidity research, bid/ask dynamics | ## OHLCV Historical Data #### Metrics | Field | Description | | --------------- | ----------------------------------------------------------- | | `price_open` | Opening price at the start of the period | | `price_high` | Highest price during the period | | `price_low` | Lowest price during the period | | `price_close` | Closing price at the end of the period | | `volume_traded` | Total volume of the base asset traded during the period | | `trades_count` | Number of individual trades that occurred during the period | #### Dimensions | Field | Description | | ------------------- | ----------------------------------------------------------- | | `symbol_id` | The trading pair identifier (e.g., `BITSTAMP_SPOT_BTC_USD`) | | `time_period_start` | Start timestamp of the candle period | | `time_period_end` | End timestamp of the candle period | | `time_open` | Exact timestamp of the first trade in the period | | `time_close` | Exact timestamp of the last trade in the period | ## Trades Historical Data #### Metrics | Field | Description | | ------- | ------------------------------- | | `price` | Execution price of the trade | | `size` | Volume of the base asset traded | #### Dimensions | Field | Description | | --------------- | ------------------------------------------------ | | `symbol_id` | The trading pair identifier | | `time_exchange` | Timestamp reported by the exchange | | `time_coinapi` | Timestamp recorded by Coin API | | `uuid` | Unique identifier for the trade | | `taker_side` | Side of the taker (buy or sell, where available) | ## Quotes Historical Data #### Metrics | Field | Description | | ----------- | ---------------------------------------------- | | `ask_price` | Best ask (sell) price at the time of the quote | | `ask_size` | Volume available at the ask price | | `bid_price` | Best bid (buy) price at the time of the quote | | `bid_size` | Volume available at the bid price | #### Dimensions | Field | Description | | --------------- | ---------------------------------- | | `symbol_id` | The trading pair identifier | | `time_exchange` | Timestamp reported by the exchange | | `time_coinapi` | Timestamp recorded by Coin API | ## Common metric combinations * **OHLCV + volume\_traded + trades\_count** — identify high-activity periods where price moved on large volume * **Quotes: ask\_price - bid\_price** — calculate spread over time to measure market liquidity * **Trades: price + size** — compute volume-weighted average price (VWAP) across a session * **OHLCV across multiple symbols** — use the **Append** transformation to combine candle data from different trading pairs for cross-asset comparison ## Use cases by role {% tabs %} {% tab title="Quant analysts" %} * Pull OHLCV data for multiple symbols and use **Append** to build a unified price history table for backtesting * Calculate rolling volatility and Sharpe ratios directly in BigQuery or a connected spreadsheet * Use trades data to analyze execution slippage and fill quality {% endtab %} {% tab title="Finance teams" %} * Track portfolio asset prices over custom date ranges and export to Excel or Google Sheets for reporting * Monitor bid/ask spreads from quotes data to assess liquidity risk for crypto holdings * Schedule daily OHLCV pulls to maintain an up-to-date price ledger {% endtab %} {% tab title="Researchers & AI users" %} * Pipe OHLCV or trades data into ChatGPT, Claude, or Gemini to detect patterns and generate plain-language market summaries * Use Perplexity or OpenClaw to ask questions directly over your historical trade data * Combine multiple entities with **Join** to enrich trade records with contemporaneous quote data {% endtab %} {% endtabs %} ## Platform-specific notes * Symbol IDs are exchange-specific — `BITSTAMP_SPOT_BTC_USD` and `COINBASE_SPOT_BTC_USD` are different symbols even for the same asset pair * The time interval (period) parameter only applies to OHLCV data — trades and quotes return tick-level records * Leaving the end date empty will pull data up to the current time, which is useful for scheduled incremental flows * Very short time intervals (e.g., 1-second candles) over long date ranges can produce millions of rows — use the record limit parameter to control output size * Coin API's free tier has rate limits and a cap on historical data depth; paid plans unlock full historical coverage --- # Agent Instructions This documentation is published with GitBook. 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