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Market trading doesn’t occur in a vacuum. It takes place amid a backdrop of virtual and physical world market events and within the context of the price/time data series of thousands of indices and instruments.

It is essential for crypto traders to understand this, and thus understand why it is essential to review and analyze historical data while managing trades. ‌In fact, given the volatile and complex nature of the crypto markets, historical data becomes even more important than it is in the more established markets.

First, what is historical data? ‌ For the most part, when someone uses the term historical data in a trading context, they are usually referring to a time series of price and volume information.‌ In other words, how many coins were traded at what price and over what time period.

Each individual trade is recorded and listed in order based on the time of the‌ trade. ‌ This is the heart of historical data, and many other metrics can be derived from this basic info. ‌There are also other types of crypto historical trading data, which we will discuss a bit further below.

Use cases of historical crypto data

Trend analysis 

Historical crypto data can help you identify patterns in a crypto’s price movement and trends. Knowing how to properly interpret these trends can inform profitable trading strategies. ‌‌As the old saying goes, “The trend is your friend.”


Historical crypto data is the basis for most numerically-based forecasting models. Accurate forecasting is, of course, very valuable because it’s like getting a sneak peek at tomorrow’s newspaper.

Risk management

Historical crypto data can help you measure the volatility (and therefore risk) associated with a particular trade or investment. The data can also help you make decisions on trade entry and exit points. 


You can use historical crypto data to compare a crypto’s performance against its peers or the overall market in order to identify whether it is under- or over-performing. Obviously, time periods are important here, so the greater the time length of your historical data, the more options for comparison you have. 

Trade strategy backtesting 

As you manage your portfolio, you can use historical crypto data to test the effectiveness of different investment strategies. By applying each strategy to historical data, you can see how it would have performed in the past, providing insight into its potential future profitability. ‌Proper backtesting requires at least three years of data, and more, if possiblel. Many centralized exchanges don't keep more than a month or two of historical data, so it's important to select a data provider that has collected significant historical data.

Using historical crypto data is no guarantee that you’ll become a profitable trader. But without it, let’s face it, you’re just guessing.


Comprehensive granular historical on-chain and market data enables you to generate essential accounting documentation, such as balance sheets, income statements, cash flow statements. 

Regulatory Compliance 

To ensure regulatory compliance, you may need to access data stored across multiple blockchains as well as centralized and decentralized exchanges.‌ Amberdata provides comprehensive, historical and real-time on-chain and market data, eliminating the need to source and integrate data from multiple vendors. ‌We are the only digital asset data provider to do so.

Tax Compliance 

Historical on-chain and market data help you comply with tax laws, understand and report on your tax exposure, and easily respond to audits.

Types of historical crypto data

Historical data for crypto is broader than just ‌historical trading prices and volumes of particular cryptocurrencies. This data can include other market data from centralized and decentralized exchanges, as well as on-chain transaction data. The most common historical crypto data is:

    • Trade history - A record of all transactions for a particular crypto that includes the price, number of units traded, and the time of the transaction.
    • Price - The most fundamental bit of data. This is the cost of a particular crypto at a particular instant, priced either in a specific fiat currency (such as U.S. dollars) or another crypto (such as Bitcoin or Ether).
    • Price change - The difference in the price of a cryptocurrency over a specific period, expressed either in absolute terms or‌ as a percentage.
    • Highs/lows - These are the highest and lowest prices at which a cryptocurrency traded during a specific period (“High of the day; Low of the day”).
  • Open, High, Low, Close, and Volume (OHLCV) - An aggregated form of market data, OHLCV data includes five data points: the Open and Close are the first and the last prices during a specified interval. High and Low are the highest and lowest trade prices during that interval. Volume is the total amount traded during the interval. Visually, this data is usually shown as a candlestick chart. Amberdata provides OHLCV data with minutely, hourly, or daily granularity.
  • Volume-Weighted Average Price (VWAP): VWAP is calculated during a specific trading session by taking the total dollar value of trading in the asset and dividing it by the volume of trades for the specified period of time. Institutional traders use VWAP to ensure that their trades do not move the price of the crypto they are trading too extremely. VWAP provides traders with insight into both the trend and value of a crypto. Amberdata provides VWAP data aggregated minutely, hourly, or daily for all exchanges we cover, with historical data back to 2012 for some exchanges.
  • Time-Weighted Average Price (TWAP): The average trading price of a crypto over a specified time. TWAP provides traders with insight into both the trend and value of an asset. Amberdata provides TWAP data aggregated by minute, hour, or day for all decentralized exchanges we cover, with historical data as far back as the genesis block for any of our supported networks. 
    • Trade volume - The number of units of a particular crypto traded during a given period. High trading volume, of course, indicates a high level of activity.
    • Market capitalization - The total value of all units of a crypto in circulation. Market Cap equals the current price of the cryptocurrency multiplied by the number of coins in circulation.
  • Reference quotes: Because the same crypto pair can simultaneously trade at different prices on different exchanges, Amberdata provides “Reference Quotes” to give traders a feel for an accurate crypto trade pair price. ‌‌These quotes are the average ‌“Mid prices” across exchanges for each pair. Mid Price = (Ask + Bid) / 2). We provide Reference Quotes for every pair across every exchange we support in the spot markets.  While prices, TWAP, and VWAP are all calculated based on post-trade data, Reference Quotes are calculated based on pre-trade data. ‌ We enable our users to determine which exchanges are included in these calculations, and also allow them to see a list of the sources if none are specified. Amberdata is one of the only data providers who offers this kind of pre-trade price data in real-time.
  • Order book - A list of open buy and sell orders for a cryptocurrency. Open orders are orders in line to be executed.

There are also other forms of historical crypto data:

  • Network metrics - These include hashrate, issuance, miner activity, fees, supply, asset, and address activity. These metrics can tell you about the state and health of‌ networks and their assets.
  • Blockchain data - Events, logs, and transactions for each digital asset on a chain. 
  • Mempool and pending transactions - A window into the future. A blockchain mempool (short for memory pool) temporarily stores unconfirmed transactions before they are added to the blockchain. You can think of a mempool as a temporary holding pen for transactions. You can watch transactions in-flight before they are incorporated into a block, as well as identify large movements to or from exchanges, counterparties, or addresses of interest.

Token data

  • Token information - Comprehensive token information for various tokens including token name, symbol, contract address, decimals, total supply, circulating supply, and more.
  • Token transfers - A token transfer occurs when tokens are moved from one blockchain address to another, like when you transfer some tokens to a friend.  The data captured includes the sender‌, receiver, amount, transaction hash, and timestamp.
  • Token holders - Basic data on the holders of tokens, such as the number of holders, holder addresses, and the number of tokens held by each address.
  • Token analytics - Basic data such as price, volume, market cap, trading volume, and more.

Various key on-chain indicators

On-chain market fundamentals and catalysts that help inform trading decisions. Some of these indicators are:

  • Network value to transactions (NVT) - This describes the relationship between market cap and transaction volume over a specific period. Various moving average signals can be created with NVT data.
  • Uniques - Number of unique addresses transacting on a blockchain. Each address implies a unique user.
  • Risk-adjusted returns - Risk-adjusted return is a calculation of an investment’s return or potential return compared to cash or cash equivalents. Typically, the higher the adjusted return, the better.
  • Volatility - Measures how much a crypto’s price fluctuates. ‌High volatility can generate large gains and large losses.
  • Asset velocity - The total transaction volume of a cryptocurrency divided by its market capitalization during a particular time period. Velocity can give you an idea of how that cryptocurrency is being used. ‌ Some investors use velocity to try to arrive at a “fair value” of the crypto. 

Trade volume data

Trade volume is the amount of a particular crypto traded during a time period. This is extremely useful for traders and investors. 

  • Liquidity - High trade volume equals high liquidity, meaning it’s easy to make a trade at the current price. Low volume crypto can be difficult to trade without causing significant price movement.‌‌‌‌ (That is, your order itself pushes the price.)
  • Market activity - High trading volumes indicate a high level of interest or activity in a crypto, for any number of reasons.
  • Trend confirmation - Trading volume can also be used to confirm price trends. For example, many traders consider a rising price combined with increased trading volume to be a bullish signal.
  • Volatility - High trading volume can sometimes be associated with high volatility, since large volumes of trades can create rapid price movement.

Network data 

Crypto network data is the info on the transactions, blocks, and overall state of a particular blockchain network. This data can help you make decisions about the health, usage, scalability, security, and trends of specific crypto tokens. Some of the key components of crypto network data are:

  • Transaction data - High transaction activity indicates a high level of network usage.
  • Block data - For “Proof of Work” blockchains (like Bitcoin), every few minutes the blockchain’s validators (“miners”) solve a computation problem that then permanently writes a series of transactions to a block in that blockchain. ‌ For “Proof of Stake” blockchains (like Ethereum), validators are chosen randomly from among those users who “stake” their crypto, with consideration given to the value of their staked crypto. In either case, when a block is created, its size, the number of transactions in it, and the time it took to mine or validate it are all recorded. Aggregated block data gives you an idea of the network’s scalability and efficiency. 
  • Hash rate - Hash Rate measures the amount of computing power necessary to solve each computation problem that secures the blockchain network. The higher the hash rate, the greater the blockchain’s security.
  • Active addresses - This is the number of unique addresses actively transacting on the network. A high number shows high network usage and adoption.
  • Gas prices - “Gas” is a transaction fee paid to miners who verify transactions on blockchains. Virtually all blockchains use gas, and gas price data can provide insight into network usage, congestion, and transaction costs.
  • Staking data - For Proof of Stake networks, the number of staked tokens, staking rewards, and a number of validators can help you analyze network participation and security.

Order book data

Crypto order book data is the real-time record of pending buy/sell orders for a crypto on an exchange. This is extremely valuable data, providing a vision on market depth and liquidity. ‌Accessing order book data is like seeing tomorrow’s weather forecast or hearing a travel report on road conditions up ahead.

The key components of order book data are buy orders (bids), sell orders (asks), order size (quantity), and order price.

  • Buy orders (bids) - Orders placed by buyers willing to purchase a cryptocurrency at a certain price.
  • Sell orders (asks) - Orders placed by sellers willing to sell a cryptocurrency at a certain price.
  • Order size - The amount of cryptocurrency to be bought or sold at the specified price.
  • Cumulative size - Cumulative order sizes at different price levels. This helps you determine how much crypto would need to be bought or sold to move the price to a target level.

How historical crypto data is collected

Historical crypto data is collected from a variety of sources. Some of the main data sources that contribute to the process are:

Crypto exchange APIs

These are a fountainhead of historical crypto data. Millions of trades are made every day on exchanges, and these exchanges collect and store a vast amount of trade data. Most exchanges provide APIs by which you can easily access this data, although some centralized exchanges only keep two to three months of data. Some exchanges provide historical data directly, while others allow only real-time streams, in which case you must collect the data over time. ‌Most third party providers, on the other hand, have considerable historical data available.

Blockchain APIs

Because blockchain blocks, addresses, and transactions are publicly available, you can harvest this data directly. ‌ However, usually it’s an enormous amount of data that is difficult to manage and decipher. For most financial institutions, investing in the creation and maintenance of the infrastructure to run blockchain nodes and collect the data is an untenable proposition.

Challenges in collecting historical crypto data

As you’ve seen, it can be quite valuable to aggregate and analyze as much historical crypto data as possible. ‌However, collecting data from a variety of sources can be challenging for the following reasons:

Data accuracy and reliability 

Unlike in traditional financial markets, where companies must by law provide accurate data, in crypto, data accuracy isn’t always a certainty. Data reported by exchanges might be inaccurate or misleading due to technical errors, manipulation (such as wash trading), poor reporting systems, or a host of other possibilities. This is why it is important to focus on the most reliable exchanges for market data.

Data consistency and quality 

Ensuring the consistency and quality of data from multiple sources is difficult. Different formats, granularity, and data definitions can be bedeviling. Cleaning and standardizing the data can be time-consuming and expensive.

Data availability 

Not all exchanges or data sources keep substantial (many months or years) historical crypto data, and some only provide real-time data.

Data accessibility 

Not all data is free. Some historical crypto data sources restrict access to their data, either through paywalls or by limiting the use of their API. 

Market fragmentation

The crypto market is highly fragmented, with hundreds of exchanges around the world. Aggregating data across all these exchanges is complex and resource intensive.

Technical complexity 

Collecting data from diverse sources requires various technical skills. You need experience with APIs, databases, and more. Creating the infrastructure and acquiring the personnel to do this is costly and complicated.


Even with the necessary skills, collecting and maintaining a database of historical crypto data can be costly, requiring large computing power and storage.

Amberdata crypto historical data API

When trading the crypto markets, nothing is more critical to success than having clean, accurate, and comprehensive data to work with. ‌Amberdata delivers data and insights into blockchain networks, crypto markets, and decentralized finance, empowering financial institutions with real-time, historical, fundamental, and market data for research, trading, risk, analytics, reporting, and compliance.

Contact us today for a demo or more information on how we can help you.

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