The data is provided in a .csv file using the FileWhooper service. This service is currently only available for Windows and macOS filesystem. If you need the data using a linux system, please contact me.

More Info:

What are aggregate trades? If multiple trades are filled at the same millisecond, from the same order and at the same price, these trades are stored in one single aggregate trade.

What do the columns mean? id Each trade on the exchange server has an unique id. This id is directly fetched from the exchange server to guarantee gapless and consistent data.

time Timestamp in milliseconds when the trade happened on the exchange server asa provided by the exchange. Check https://currentmillis.com/ to find out how to translate this timestamp into a human readable format.

price Price per base currency in the given quote currency (here: USDT).

amount Quantity that was traded, given in base currency.

sell Can be True or False. If "True", then a price taker placed a market sell order to take an existing buy offer.

Browse Options on Bitcoin Futures (BTC) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

The CME Group Market Data Platform (MDP) 3.0 disseminates event-based bid, ask, trade, and statistical data for CME Group markets and also provides recovery and support services for market data processing. MDP 3.0 includes the introduction of Simple Binary Encoding (SBE) and Event Driven Messaging to the CME Group Market Data Platform. Simple Binary Encoding (SBE) is based on simple primitive encoding, and is optimized for low bandwidth, low latency, and direct data access. Since March 2017, MDP 3.0 has changed from providing aggregated depth at every price level (like CME's legacy FAST feed) to providing full granularity of every order event for every instrument's direct book. MDP 3.0 is the sole data feed for all instruments traded on CME Globex, including futures, options, spreads and combinations. Note: We classify exchange-traded spreads between futures outrights as futures, and option combinations as options.

Origin: Directly captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Daily cryptocurrency data (transaction count, on-chain transaction volume, value of created coins, price, market cap, and exchange volume) in CSV format. The data sample stretches back to December 2013. Daily on-chain transaction volume is calculated as the sum of all transaction outputs belonging to the blocks mined on the given day. “Change” outputs are not included. Transaction count figure doesn’t include coinbase transactions. Zcash figures for on-chain volume and transaction count reflect data collected for transparent transactions only. In the last month, 10.5% (11/18/17) of ZEC transactions were shielded, and these are excluded from the analysis due to their private nature. Thus transaction volume figures in reality are higher than the estimate presented here, and NVT and exchange to transaction value lower. Data on shielded and transparent transactions can be found here and here. Decred data doesn’t include tickets and voting transactions. Monero transaction volume is impossible to calculate due to RingCT which hides transaction amounts.

CoinAPI delivers enterprise-grade data infrastructure specifically designed for quantitative trading, providing real-time and historical data feeds from over 350+ exchanges through unified, scalable APIs.

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📊 Market Coverage & Data Types: ◦ Real-time and historical data since 2010 (for chosen assets) ◦ Full order book depth (L2/L3) ◦ Trade-by-trade data ◦ OHLCV across multiple timeframes ◦ Market indexes (VWAP, PRIMKT) ◦ Exchange rates with fiat pairs ◦ Spot, futures, options, and perpetual contracts ◦ Coverage of 90%+ global trading volume

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CoinAPI serves hundreds of institutions worldwide, from trading firms and hedge funds to research organizations and technology providers. Our commitment to data quality and technical excellence makes us the trusted choice for the cryptocurrency market's data needs.

Our Market Data covers historical and real-time data. For CEXs, our data spans back to 2015, and for DEXs, we cover since the genesis trade. We cover every instrument on any exchange, so if it's traded, we cover it.

We understand you need to access the data you want, when and where you need it. With this in mind, we built our Market Data with several delivery options, including a robust streaming service offering the most advanced live data distribution in the cryptocurrency industry, as well as REST API, CSV via cloud services, and BigQuery.

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A proven enterprise-grade solution We prioritize the needs of enterprises in our product development, ensuring our solutions meet the requirements of larger organizations seeking best-in-class crypto data.

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Flexible to meet your needs Flexibility lies at the heart of our product and is fundamental to how crypto data can deliver value across industries and use cases. Living this philosophy, we’re always building custom options that can help you achieve your specific objectives. Whether it’s tailoring a package to meet your requirements, or adapting infrastructure to support your use case, our data and product teams are on-hand to help you find the best way to achieve your priority outcomes.

We monitor and process Currency data, all major Forex pairs, 10K+ Cryptocurrencies, and Bitcoin Prices data with seamless integration. for flexible market analysis or custom use cases.

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On-Chain Metrics.xlsx contains a description of the on-chain metrics. Merged_df.xlsx is the main data source containing the BTC prices, the on-chain metrics and the sentiment scores. btc_twets_new.csv and training.1600000.processed.noemoticon.csv are the data sources for calculating the sentiment scores. Sentiment_Analysis.py contains the code to calculate the sentiment scores. The scores are in Merged_df.xlsx BTC_Prediction.py contains the implementation of the main approach described in the paper, especially in Fig. 11.

3MEth Dataset OverviewSection 1: Token TransactionsThis section provides 303 million transaction records from 3,880 tokens and 35 million users on the Ethereum blockchain. The data is stored in 3,880 CSV files, each representing a specific token. Each transaction includes the following information:Sender and receiver wallet addresses: Enables network analysis and user behavior studies.Token address: Links transactions to specific tokens for token-specific analysis.Transaction value: Reflects the number of tokens transferred, essential for liquidity studies.Blockchain timestamp: Captures transaction timing for temporal analysis.Apart from the large dataset, we also provide a smaller CSV file containing 267,242 transaction records from 29,164 wallet addresses. This smaller dataset involves a total of 1,194 tokens, covering the time period September 2016 to November 2023. This detailed transaction data is critical for studying user behavior, liquidity patterns, and tasks such as link prediction and fraud detection.Section 2: Token InformationThis section offers metadata for 3,880 tokens, stored in corresponding CSV files. Each file contains:Timestamp: Marks the time of data update.Token price: Useful for price prediction and volatility studies.Market capitalization: Reflects the token's market size and dominance.24-hour trading volume: Indicates liquidity and trading activity.Section 3: Global Market IndicesThis section provides macro-level data to contextualize token transactions, stored in separate CSV files. Key indicators include:Bitcoin dominance: Tracks Bitcoin's share of the cryptocurrency market.Total market capitalization: Measures the overall market's value, with breakdowns by token type.Stablecoin market capitalization: Highlights stablecoin liquidity and stability.24-hour trading volume: A key measure of market activity.These indices are essential for integrating global market trends into predictive models for volatility and risk-adjusted returns.Section 4: Textual IndicesThis section contains sentiment data from Reddit's Ethereum community, covering 7,800 top posts from 2014 to 2024. Each post includes:Post score (net upvotes): Reflects engagement and sentiment strength.Timestamp: Aligns sentiment with price movements.Number of comments: Gauges sentiment intensity.Sentiment indices: Sentiment scores computed using methods detailed in the data preprocessing section.The full Reddit textual dataset is available upon request; please contact us for access. Alternatively our open-source repository includes a tool to guide users in collecting Reddit data. Researchers are encouraged to apply for a Reddit API Key and adhere to Reddit's policies. This data is valuable for understanding social dynamics in the market and enhancing sentiment analysis models that can explain market movements and improve behavioral predictions.

Browse iShares Bitcoin Trust (IBIT) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants. This proprietary feed provides additional information about activity on the Nasdaq market that is not present on data sourced from the SIPs. Nasdaq TotalView-ITCH provides information about every order on the book, allowing you to model quote lifetimes, queue dynamics and depth at every price level - all of which are not possible with the SIPs. Moreover, Nasdaq TotalView-ITCH data generally disseminates faster in real-time, and provides more accurate and precise exchange-side timestamping. TotalView-ITCH also disseminates the Net Order Imbalance Indicator (NOII) for the Nasdaq Opening and Closing Crosses and Nasdaq IPO/Halt Cross. Databento captures and normalizes the Nasdaq TotalView-ITCH feed losslessly, and combines it with other US equities proprietary feeds to consolidate a faster, more granular, synthetic NBBO than the SIPs. This dataset and feed is not adjusted for corporate actions and delistings, allowing the user to perform simulation and backtests without look-ahead bias. In addition, we also aggregate top of book (TBBO) and bar aggregate (OHLCV) data from the original data.

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

This dataset contains several files:dataset.tar.gz: A compressed PostgreSQL database representing a graph.addresses.csv: A list of approximately 100,000 labeled Bitcoin addresses.BitcoinTemporalGraph (dataset.tar.gz)This dataset represents a graph of value transfers between Bitcoin users. The nodes represent entities/users, and the edges represent value transfers or transactions between these entities. The graph is temporal and directed.Usage:Decompress the archive: "pigz -p 10 -dc dataset.tar.gz | tar -xvf -"Restore the tables into an existing PostgreSQL database using the pg_restore utility: "pg_restore -j number_jobs -Fd -O -U database_username -d database_name dataset"Ensure substantial storage for the database: 40GB for node_features and 80GB for transaction_edges (including indexes)Dataset DescriptionThe database contains two tables: node_features (approximately 252 million rows) and transaction_edges (approximately 785 million rows).Columns for node_features table:alias: Identifier of the nodedegree: Degree of the nodedegree_in: Number of incoming edges to the nodedegree_out: Number of outgoing edges from the nodetotal_transaction_in: Total count of value transfers received by the nodetotal_transaction_out: Total count of value transfers initiated by the nodeAmounts are expressed in satoshis (1 satoshi = 10^-8 Bitcoin):min_sent: Minimum amount sent by the node during a transactionmax_sent: Maximum amount sent by the node during a transactiontotal_sent: Total amount sent by the node during all transactionsmin_received: Minimum amount received by the node during a transactionmax_received: Maximum amount received by the node during a transactiontotal_received: Total amount received by the node during all transactionslabel: Label describing the type of entity represented by the nodeTransactions on the Bitcoin network are stored in the public ledger named the "Bitcoin Blockchain". Each transaction is recorded in a block, with the block index indicating the transaction's position in the blockchain.first_transaction_in: Block index of the first transaction received by the nodelast_transaction_in: Block index of the last transaction received by the nodefirst_transaction_out: Block index of the first transaction sent by the nodelast_transaction_out: Block index of the last transaction sent by the nodeNodes can represent one or more Bitcoin addresses (pseudonyms used by Bitcoin users). A real entity often uses multiple addresses. The dataset contains only transactions between nodes (outer transactions), but provides information about inner transactions (transactions between addresses controlled by the same node).cluster_size: Number of addresses represented by the nodecluster_num_edges: Number of transactions between the addresses represented by the nodecluster_num_cc: Number of connected components in the transaction graph of the addresses represented by the nodecluster_num_nodes_in_cc: Number of non-isolated addresses in the clusterColumns in the transaction_edges table:a: Node alias of the senderb: Node alias of the recipientreveal: Block index of the first transaction from a to blast_seen: Block index of the last transaction from a to btotal: Total number of transactions from a to bmin_sent: Minimum amount sent (in satoshis) in a transaction from a to bmax_sent: Maximum amount sent (in satoshis) in a transaction from a to btotal_sent: Total amount sent (in satoshis) in all transactions from a to bDataset of Bitcoin Labeled Addresses (addresses.csv)This file contains 103,812 labeled Bitcoin addresses with the following columns:address: Bitcoin addressentity: Name of the entitycategory: Type of the entity (e.g., individual, bet, ransomware, gambling, exchange, mining, ponzi, marketplace, faucet, bridge, mixer)source: Source used to label the address

The data is provided in a .csv file per pair using the FileWhooper service. This service is currently only available for Windows and macOS filesystem. If you need the data using a linux system, please contact me.

More Info:

What are aggregate trades? If multiple trades are filled at the same millisecond, from the same order and at the same price, these trades are stored in one single aggregate trade.

What do the columns mean? id Each trade on the exchange server has an unique id. This id is directly fetched from the exchange server to guarantee gapless and consistent data.

time Timestamp in milliseconds when the trade happened on the exchange server asa provided by the exchange. Check https://currentmillis.com/ to find out how to translate this timestamp into a human readable format.

price Price per base currency in the given quote currency (here: USDT).

amount Quantity that was traded, given in base currency.

sell Can be True or False. If "True", then a price taker placed a market sell order to take an existing buy offer.