This dataset includes daily historical price data for Bitcoin (BTC-USD) from 2014 to 2025, obtained through web scraping from the Yahoo Finance page using Selenium. The primary data source can be accessed at Yahoo Finance - Bitcoin Historical Data . The dataset contains daily information such as opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and trading volume (Volume).

About Bitcoin: Bitcoin (BTC) is the world's first decentralized digital currency, introduced in 2009 by an anonymous creator known as Satoshi Nakamoto. It operates on a peer-to-peer network powered by blockchain technology, enabling secure, transparent, and trustless transactions without the need for intermediaries like banks. Bitcoin's limited supply of 21 million coins and its growing adoption have made it a popular asset for investment, trading, and as a hedge against inflation.

We are excited to share this dataset and look forward to seeing the insights it can provide. We hope it will inspire collaboration and innovation within the community. By leveraging this daily data, we can explore trends, develop predictive models, and design innovative trading strategies that deepen our understanding of Bitcoin's market behavior. Together, we can unlock new opportunities and contribute to the collective advancement of cryptocurrency research and analysis.

Context

This minute by minute historical dataset of bitcoin prices offers a wealth of information for data scientists and analysts. In addition to the OHLC prices for each minute, this dataset also includes the volume of bitcoin traded during that time period. This granular data, going back to 2015, allows for in-depth analysis of the market fluctuations and trends of the world's most popular cryptocurrency.

With this dataset, researchers can study the underlying mechanisms of the bitcoin network, traders can gain a better understanding of market movements, and investors can make more informed decisions about their investments. The open, high, low, and close prices, as well as the volume data, provide a wealth of information for analyzing the market and identifying potential opportunities.

Whether you're looking to gain a competitive edge as a trader, conduct research on the bitcoin market, or simply want to learn more about the world of cryptocurrency, this dataset is a valuable resource. With its rich and detailed data, you'll be able to dive deep into the world of bitcoin and uncover insights that can help you make better decisions.

Content

• Timestamp: This is the UNIX timestamp or the "Epoch Time", number of seconds elapsed since 00:00:00 UTC on 1 January 1970.
• Date: Date and time of price recording.
• Open - This is the opening price of the time period (in US Dollars).
• High - This is the highest price of the time period (in US Dollars).
• Low - This is the lowest price of the time period (in US Dollars).
• Close - This is the closing price of the time period (in US Dollars).
• Volume BTC - This is the volume of ₿ transacted in the time interval.
• Volume USD - This is the volume of $ transacted in the time interval.

The following dataset contains the attributes: Date: Specific date to be observed for the corresponding price. Open: The opening price for the day High: The maximum price it has touched for the day Low: The minimum price it has touched for the day Close: The closing price for the day percent_change_24h: Percentage change for the last 24hours Volume: Volume of Bitcoin traded at the date Market Cap: Market Value of traded Bitcoin

The Bitcoin (BTC) price again reached an all-time high in 2025, as values exceeded over 114,128.35 USD on August 6, 2025. Price hikes in early 2025 were connected to the approval of Bitcoin ETFs in the United States, while previous hikes in 2021 were due to events involving Tesla and Coinbase, respectively. Tesla's announcement in March 2021 that it had acquired 1.5 billion U.S. dollars' worth of the digital coin, for example, as well as the IPO of the U.S.'s biggest crypto exchange, fueled mass interest. The market was noticeably different by the end of 2022, however, after another crypto exchange, FTX, filed for bankruptcy.Is the world running out of Bitcoin?Unlike fiat currency like the U.S. dollar - as the Federal Reserve can simply decide to print more banknotes - Bitcoin's supply is finite: BTC has a maximum supply embedded in its design, of which roughly 89 percent had been reached in April 2021. It is believed that Bitcoin will run out by 2040, despite more powerful mining equipment. This is because mining becomes exponentially more difficult and power-hungry every four years, a part of Bitcoin's original design. Because of this, a Bitcoin mining transaction could equal the energy consumption of a small country in 2021.Bitcoin's price outlook: a potential bubble?Cryptocurrencies have few metrics available that allow for forecasting, if only because it is rumored that only a few cryptocurrency holders own a large portion of the available supply. These large holders - referred to as 'whales'-are' said to make up two percent of anonymous ownership accounts, while owning roughly 92 percent of BTC. On top of this, most people who use cryptocurrency-related services worldwide are retail clients rather than institutional investors. This means outlooks on whether Bitcoin prices will fall or grow are difficult to measure, as movements from one large whale are already having a significant impact on this market.

The dataset used in this research is a historical record of Bitcoin, Ethereum, and Litecoin’s daily trading activity, containing essential financial metrics for each date. This sample includes the following columns: Date: The specific day of each recorded entry, showing a continuous timeline. Open: The price of currencies at the start of the trading day. High: The highest price of currencies reached during the day. Low: The lowest price of currencies traded throughout the day. Close: The closing price of the currencies at the end of the trading day. Volume: The total trading volume, indicating the number of currencies traded that day in units. Market Cap: The total market capitalization of currencies, calculated as the total supply multiplied by the closing price.

This dataset contains a comprehensive collection of historical price records for the top 1000 cryptocurrencies. The data in this dataset is updated daily, providing a reliable and up-to-date source of information for cryptocurrency traders, researchers, and enthusiasts.

Each file in the dataset includes the following columns: date, open price, high price, low price, closing price, adjusted closing price, and trading volume. These columns provide a detailed picture of the daily price movements and trading activity of each cryptocurrency in the dataset.

The "date" column indicates the day on which the price data was recorded, while the "open" column provides the opening price of the cryptocurrency for that day. The "high" and "low" columns indicate the highest and lowest prices of the cryptocurrency on that day, respectively. The "close" column represents the closing price of the cryptocurrency on that day, while the "adjusted close" column takes into account any dividends or other corporate actions that may have affected the price. Finally, the "volume" column shows the trading volume of the cryptocurrency on that day.

With this dataset, users can analyze and visualize the performance of individual cryptocurrencies, compare them to one another, and track trends over time. The data is ideal for use in machine learning models, predictive analytics, and other data-driven applications.

Description:

This dataset offers a detailed view of Bitcoin's price history, including daily open, high, low, and close prices, as well as trading volumes. It includes a comprehensive set of market data points, helping users analyze Bitcoin's price fluctuations over time and study market dynamics, volatility, and long-term trends.

By tracking Bitcoin's price history alongside blockchain trends, this dataset helps identify correlations between market events and blockchain activities, making it ideal for trend analysis and market forecasting.

Analyze the growth of Bitcoin from its inception to the present by exploring price changes, trading volume, and market capitalization. This dataset includes daily data, allowing users to examine how Bitcoin has evolved, the periods of significant price increases, and the overall market sentiment across time.

This dataset includes real-time or near real-time data on Bitcoin’s price, volume traded, and transaction details, providing up-to-date information for market analysis. It's perfect for those looking to perform real-time market analysis, back-test trading strategies, or monitor Bitcoin’s performance against other cryptocurrencies.

1) Data Introduction • The Bitcoin Historical Dataset is a cryptocurrency time-series dataset that summarizes the history of Bitcoin (BTC) minutes-by-minute transactions in a tabular format for 2017, including key transaction information such as market price and volume per minute.

2) Data Utilization (1) Bitcoin Historical Dataset has characteristics that: • Each row contains key market and transaction information, including Unix timestamps, dates (UTC), symbols, open, high, low, close, BTC, and USD. • The data is an ultra-high resolution time series structure that is well structured for price volatility analysis, ultra-short prediction, deep learning time series model learning, and more. (2) Bitcoin Historical Dataset can be used to: • Bitcoin Price Forecasting and Trading Strategies: Using minute-by-minute market price data, it can be used to develop deep learning-based price forecasting and auto-trading strategies such as LSTM and reinforcement learning. • Analyzing Volatility and Market Patterns: High-frequency trading data can be applied to researching cryptocurrency market structure, including market volatility, detection of abnormal trading, and transaction volume-based pattern analysis.

OHLCV is an abbreviation for the five critical data points: Open, High, Low, Close, and Volume. It refers to the key points in analyzing an asset such as Bitcoin (BTC) in the market over a specified time. The dataset is important for not only traders and analysts but also for data scientists who work on BTC market prediction using artificial intelligence. The 'Open' and 'Close' prices represent the starting and ending price levels, while the 'High' and 'Low' are the highest and lowest prices during that period (a daily time frame (24h)). The 'Volume' is a measure of the total number of trades. This dataset provides five OHLCV data columns for BTC along with a column called "Next day close price" for regression problems and machine learning applications. The dataset includes daily information from 1/1/2012 to 8/6/2022.

In March 2024 Bitcoin BTC reached a new all-time high with prices exceeding 73000 USD marking a milestone for the cryptocurrency market This surge was due to the approval of Bitcoin exchange-traded funds ETFs in the United States allowing investors to access Bitcoin without directly holding it This development increased Bitcoin’s credibility and brought fresh demand from institutional investors echoing previous price surges in 2021 when Tesla announced its 15 billion investment in Bitcoin and Coinbase was listed on the Nasdaq By the end of 2022 Bitcoin prices dropped sharply to 15000 USD following the collapse of cryptocurrency exchange FTX and its bankruptcy which caused a loss of confidence in the market By August 2024 Bitcoin rebounded to approximately 64178 USD but remained volatile due to inflation and interest rate hikes Unlike fiat currency like the US dollar Bitcoin’s supply is finite with 21 million coins as its maximum supply By September 2024 over 92 percent of Bitcoin had been mined Bitcoin’s value is tied to its scarcity and its mining process is regulated through halving events which cut the reward for mining every four years making it harder and more energy-intensive to mine The next halving event in 2024 will reduce the reward to 3125 BTC from its current 625 BTC The final Bitcoin is expected to be mined around 2140 The energy required to mine Bitcoin has led to criticisms about its environmental impact with estimates in 2021 suggesting that one Bitcoin transaction used as much energy as Argentina Bitcoin’s future price is difficult to predict due to the influence of large holders known as whales who own about 92 percent of all Bitcoin These whales can cause dramatic market swings by making large trades and many retail investors still dominate the market While institutional interest has grown it remains a small fraction compared to retail Bitcoin is vulnerable to external factors like regulatory changes and economic crises leading some to believe it is in a speculative bubble However others argue that Bitcoin is still in its early stages of adoption and will grow further as more institutions and governments recognize its potential as a hedge against inflation and a store of value 2024 has also seen the rise of Bitcoin Layer 2 technologies like the Lightning Network which improve scalability by enabling faster and cheaper transactions These innovations are crucial for Bitcoin’s wider adoption especially for day-to-day use and cross-border remittances At the same time central bank digital currencies CBDCs are gaining traction as several governments including China and the European Union have accelerated the development of their own state-controlled digital currencies while Bitcoin remains decentralized offering financial sovereignty for those who prefer independence from government control The rise of CBDCs is expected to increase interest in Bitcoin as a hedge against these centralized currencies Bitcoin’s journey in 2024 highlights its growing institutional acceptance alongside its inherent market volatility While the approval of Bitcoin ETFs has significantly boosted interest the market remains sensitive to events like exchange collapses and regulatory decisions With the limited supply of Bitcoin and improvements in its transaction efficiency it is expected to remain a key player in the financial world for years to come Whether Bitcoin is currently in a speculative bubble or on a sustainable path to greater adoption will ultimately be revealed over time.

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/ This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA

This dataset contains historical price data for Bitcoin (BTC) against the U.S. Dollar (USD), spanning from June 2010 to November 2024. The data is organized on a daily basis and includes key market metrics such as the opening price, closing price, high, low, volume, and market capitalization for each day.

Columns: The dataset consists of the following columns:

Date: The date of the recorded data point (format: YYYY-MM-DD). Open: The opening price of Bitcoin on that day. High: The highest price Bitcoin reached on that day. Low: The lowest price Bitcoin reached on that day. Close: The closing price of Bitcoin on that day. Volume: The total trading volume of Bitcoin during that day. Market Cap: The total market capitalization of Bitcoin on that day (calculated by multiplying the closing price by the circulating supply of Bitcoin at the time). Source: The data is sourced from Yahoo Finance.

Time Period: The data spans from June 2010, when Bitcoin first began trading, to November 2024. This provides a comprehensive view of Bitcoin’s historical price movements, from its early days of trading at a fraction of a cent to its more recent valuation in the thousands of dollars.

Use Cases:

This dataset is valuable for a variety of purposes, including:

Time Series Analysis: Analyze Bitcoin price movements, identify trends, and develop predictive models for future prices. Financial Modeling: Use the dataset to assess Bitcoin as an asset class, model its volatility, or simulate investment strategies. Machine Learning: Train machine learning algorithms to forecast Bitcoin’s future price or predict market trends based on historical data. Economic Research: Study the impact of global events on Bitcoin’s price, such as regulatory changes, technological developments, or macroeconomic factors. Visualization: Generate visualizations of Bitcoin price trends, trading volume, and market capitalization over time.

The selected variables were chosen base on the literature for time series of stock prices prediction or Forex (currency) prediction. The analises test only variables associated with the price like Bitcoin close, open, high and low price and volumn (for one representative exchange). Like Chen and Bahar, we used moving average of the variables to generate new variables in order to capture other information that could be hidden due the high noise generate characteristic of a high volatile asset. Also, like \cite{Bahar2016}, we use Gold an Death Cross, that are very common data for technical analysis.

Analysis of ‘Crypto-data-part1’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tusharsarkar/cryptodatapart1 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Things like Block chain, Bitcoin, Bitcoin cash, Ethereum, Ripple etc are constantly coming in the news articles I read. So I wanted to understand more about it and this post helped me get started. Once the basics are done, the data scientist inside me started raising questions like:

How many cryptocurrencies are there and what are their prices and valuations? Why is there a sudden surge in the interest in recent days? So what next? Now that we have the price data, I wanted to dig a little more about the factors affecting the price of coins. I started of with Bitcoin and there are quite a few parameters which affect the price of Bitcoin. Thanks to Blockchain Info, I was able to get quite a few parameters on once in two day basis.

This will help understand the other factors related to Bitcoin price and also help one make future predictions in a better way than just using the historical price.

Content

The dataset has one csv file for each currency. Price history is available on a daily basis from April 28, 2013. This dataset has the historical price information of some of the top crypto currencies by market capitalization.

Date : date of observation Open : Opening price on the given day High : Highest price on the given day Low : Lowest price on the given day Close : Closing price on the given day Volume : Volume of transactions on the given day

--- Original source retains full ownership of the source dataset ---

The dataset of this paper is collected based on Google, Blockchain, and the Bitcoin market. Generally, there is a total of 26 features, however, a feature whose correlation rate is lower than 0.3 between the variations of price and the variations of feature has been eliminated. Hence, a total of 21 practical features including Market capitalization, Trade-volume, Transaction-fees USD, Average confirmation time, Difficulty, High price, Low price, Total hash rate, Block-size, Miners-revenue, N-transactions-total, Google searches, Open price, N-payments-per Block, Total circulating Bitcoin, Cost-per-transaction percent, Fees-USD-per transaction, N-unique-addresses, N-transactions-per block, and Output-volume have been selected. In addition to the values of these features, for each feature, a new one is created that includes the difference between the previous day and the day before the previous day as a supportive feature. From the point of view of the number and history of the dataset used, a total of 1275 training data were used in the proposed model to extract patterns of Bitcoin price and they were collected from 12 Nov 2018 to 4 Jun 2021.

Bitcoin's circulating supply has grown steadily since its inception in 2009, reaching over 19.9 million coins by late July 2025. This gradual increase reflects the cryptocurrency's design, which put a limit of 21 million on the total number of bitcoins that can ever exist. This impacts the Bitcoin price somewhat, as its scarcity can lead to volatility on the market. Maximum supply and scarcity Bitcoin is unusual from other cryptocurrencies in that its maximum supply is getting closer. By July 2025, more than 90 percent of all possible Bitcoin had been created. That said, Bitcoin's circulating supply is expected to reach its maximum around the year 2140. Meanwhile, mining becomes exponentially more difficult and energy-intensive. Institutional investors In 2025, countries like the United States openly started discussing the possibility of buying bitcoins to hold in reserve. By the time of writing, it was unclear whether this would happen. Nevertheless, institutional investors displayed more interest in the cryptocurrency than before. Certain companies owned several thousands of Bitcoin tokens in 2025, for example. This and the limited number of Bitcoin may further fuel price volatility.

This dataset holds data about the Bitcoin price (in USD) since its first public trading (in 2010) until Jan 2025.

Data for 2010-2011 might be unreliable.

The dataset was compiled by merging existing datasets + adding the missing data for Jan 2025.

Analysis of ‘Ethereum Cryptocurrency Historical Dataset ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kaushiksuresh147/ethereum-cryptocurrency-historical-dataset on 30 September 2021.

--- Dataset description provided by original source is as follows ---

https://www.bernardmarr.com/img/What%20Is%20The%20Difference%20Between%20Bitcoin%20and%20Ethereum.png">

Context

Ethereum a decentralized, open-source blockchain featuring smart contract functionality was proposed in 2013 by programmer Vitalik Buterin. Development was crowdfunded in 2014, and the network went live on 30 July 2015, with 72 million coins premined.

Some interesting facts about Ethereum(ETH): - Ether (ETH) is the native cryptocurrency of the platform. It is the second-largest cryptocurrency by market capitalization, after Bitcoin. Ethereum is the most actively used blockchain. - Some of the world’s leading corporations joined the EEA(Ethereum Alliance, is a collaboration of many block start-ups) and supported “further development.” Some of the most famous companies are Samsung SDS, Toyota Research Institute, Banco Santander, Microsoft, J.P.Morgan, Merck GaA, Intel, Deloitte, DTCC, ING, Accenture, Consensys, Bank of Canada, and BNY Mellon.

Content

The dataset consists of ETH prices from March-2016 to the current date(1830days) and the dataset will be updated on a weekly basis.

Information regarding the data

The data totally consists of 1813 records(1813 days) with 7 columns. The description of the features is given below

| No |Columns | Descriptions | | -- | -- | -- | | 1 | Date | Date of the ETH prices | | 2 | Price | Prices of ETH(dollars) | | 3 | Open | Opening price of ETH on the respective date(Dollars) | | 4 | High | Highest price of ETH on the respective date(Dollars) | | 5 | Low | Lowest price of ETH on the respective date(Dollars) | | 6 | Vol. | Volume of ETH on the respective date(Dollars). | | 7 | Change % | Percentage of Change in ETH prices on the respective date | |

Acknowledgements

The dataset was extracted from investing.com

Inspiration

Experts say that ethereum has a huge potential in the future. Do you believe it? Well, let's find it by building our own creative models to predict if the statement is true.

--- Original source retains full ownership of the source dataset ---

This dataset contains historical Bitcoin (BTC/USDT) price data from Binance exchange with the following specifications:

Timezone Information: - All timestamps are in UTC (Coordinated Universal Time) - Open time format: YYYY-MM-DD HH:MM:SS.ffffff UTC - Close time format: YYYY-MM-DD HH:MM:SS.ffffff UTC

Daily Timeframe Specific: - Open time: Always shows 00:00:00.000000 UTC (start of day) - Close time: Always shows 23:59:59.999000 UTC (end of day)

Timeframes Available: - 15-minute intervals (15m) - 1-hour intervals (1h) - 4-hour intervals (4h) - 1-day intervals (1d)

Data Columns: - Open time: Opening timestamp in UTC - Open: Opening price - High: Highest price during period - Low: Lowest price during period - Close: Closing price - Volume: Trading volume - Close time: Closing timestamp in UTC - Quote asset volume: Volume in quote asset (USDT) - Number of trades: Number of trades during period - Taker buy base asset volume: Volume of taker buy orders - Taker buy quote asset volume: Volume of taker buy orders in quote asset - Ignore: Unused field

Data is automatically updated and maintained through automated scripts.

The selected variables were chosen base on the literature for time series of stock prices prediction or Forex (currency) prediction. The analises test only variables associated with the price like Bitcoin close, open, high and low price and volumn (for one representative exchange). Like Chen and Bahar, we used moving average of the variables to generate new variables in order to capture other information that could be hidden due the high noise generate characteristic of a high volatile asset. Also, like \cite{Bahar2016}, we use Gold an Death Cross, that are very common data for technical analysis.