OHLCV (Open, High, Low, Close, and Volume) is an aggregated form of data that includes five data points. The Open and Close represent the first and last price level during a specified interval, the High and Low represent the highest and lowest price reached within this interval, and the Volume refers to the total amount of assets traded during that period. This data is frequently represented using a candlestick chart, which allows traders to perform technical analyses on intraday values. We provide OHLCV data with minute, hourly, or daily granularity.

DeFi OHLCV data is a concept Amberdata has pioneered. Since there is no set “end of trading day” in crypto, it can be difficult for users to compare trading pairs on a decentralized exchange with a similar pair on a centralized one. Similar to the top centralized exchanges, we normalize trading volumes by using 12 AM UTC as the end-of-day (EOD) for DEXs and lending protocols. This allows our users to maximize their trading and arbitrage opportunities across exchanges.


For the OHLCV values, the price is always in quote and the volume unit is always in base. For example, if the pair was BTC-USD, then the price values returned are in USD and the volume value is in BTC.

API Endpoints






Our OHLCV endpoints are available via REST API for historical (time series) data as well as WebSockets for real-time data. Since we maintain our own nodes we have every event from the genesis (Ethereum) block which enables us to provide the complete historical dataset for all the lending protocols we support.

Frequently Asked Questions

What is OHLCV used for?

  • OHLCV offers a normalized view of crypto ecosystems and is often used for arbitrage between centralized and decentralized exchanges.

Why is the DEX OHLCV unique?

  • Since many users are using different pools and different decentralized exchanges, we take every liquidity pool and aggregate the prices to give a price. This, in addition to DEX-only VWAP and TWAP calculations (as centralized exchanges operate very differently), allows you to understand each price in the context of volume and time across liquidity pools.