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.

About this Dataset

This dataset contains the prices of Bitcoin every minute over a period from 2017-11-06 03:00 to 2023-03-10 2:59 (YYYY-MM-DD). The data includes the time, close time, open, high, low, close prices, the volume exchanged per minute and the number of trades per minute. It represent Bitcoin prices over 2.8 millions values. This dataset is ideal for anyone who want to track, study and analyze BTC/USDT values over more than 5 years.

Time range: From 2017-11-06 04:00 to 2023-03-40 14:00

File format: Datas are in .csv format

Columns values: - time: Date in milliseconds where observation begins - open: Opening ETH price in the minute - high: Highest ETH price in the minute - low: Lowest ETH price in the minute - close: Closing ETH price in the minute - volume: Volume exchanges between time and close_time - close_time: Date in milliseconds were observation ends

Category

Economic

Keywords

Bitcoin,BTC,#btc,Cryptocurrency,Crypto

Row Count

2808000

Price

$149.00

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.

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.

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

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

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.

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.

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.

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.

The Bitcoin (BTC) price again reached an all-time high in 2025, as values exceeded over 117,853.31 USD on July 30, 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.

Comprehensive dataset for the Layer 1 blockchain narrative, including sector-wide price performance, trading volume, volume to market cap ratios, and correlation data for tokens like BTC, ETH, SOL, and others.

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.

Description 📊

This dataset provides a comprehensive historical record of Bitcoin price movements in USD over time. The data has been sourced from Yahoo Finance, a reputable financial data provider, and includes a range of valuable information for anyone interested in analyzing or understanding the cryptocurrency market.

Data Columns 📈

1. Date:📅 This column represents the date of each recorded data point. It serves as the timestamp for each observation, allowing users to track Bitcoin's price changes over time.

2. Closing Price (USD):💰 The closing price is the last traded price of Bitcoin in USD at the end of each trading day. It is a crucial metric for investors and traders, as it reflects the market sentiment and overall performance for that specific day.

3. 24h Open (USD):🌄This column represents the opening price of Bitcoin in USD for the given 24-hour trading period. The opening price is the value at which Bitcoin started trading at the beginning of the day, and it can provide insights into market sentiment and potential price trends.

4. 24h High (USD):🚀 The 24-hour high price indicates the highest price level reached by Bitcoin in USD within the given 24-hour trading window. It is valuable for identifying the day's price volatility and potential price resistance levels.

5. 24h Low (USD):📉 This column represents the lowest price level Bitcoin reached in USD during the 24-hour trading period. The 24-hour low is crucial for identifying potential support levels and understanding the cryptocurrency's price range for the day.

Analyzing this dataset can offer insights into Bitcoin's historical price trends, volatility, and potential trading strategies. Researchers and analysts can use this data to perform technical and fundamental analyses, build predictive models, or gain a better understanding of the cryptocurrency market's behavior over time.

However, It's important to note that Bitcoin operates within an open market framework, and any analysis or strategies developed should not be considered as financial advice.

This dataset is your playground for building models, crafting algorithms, and enhancing your data analysis skills. Dive in, explore, and enjoy the learning process. Happy data exploration!🚀📈💡

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.

This dataset contains historical price data for the top global cryptocurrencies, sourced from Yahoo Finance. The data spans the following time frames for each cryptocurrency:

BTC-USD (Bitcoin): From 2014 to December 2024 ETH-USD (Ethereum): From 2017 to December 2024 XRP-USD (Ripple): From 2017 to December 2024 USDT-USD (Tether): From 2017 to December 2024 SOL-USD (Solana): From 2020 to December 2024 BNB-USD (Binance Coin): From 2017 to December 2024 DOGE-USD (Dogecoin): From 2017 to December 2024 USDC-USD (USD Coin): From 2018 to December 2024 ADA-USD (Cardano): From 2017 to December 2024 STETH-USD (Staked Ethereum): From 2020 to December 2024

Key Features:

Date: The date of the record. Open: The opening price of the cryptocurrency on that day. High: The highest price during the day. Low: The lowest price during the day. Close: The closing price of the cryptocurrency on that day. Adj Close: The adjusted closing price, factoring in stock splits or dividends (for stablecoins like USDT and USDC, this value should be the same as the closing price). Volume: The trading volume for that day.

Data Source:

The dataset is sourced from Yahoo Finance and spans daily data from 2014 to December 2024, offering a rich set of data points for cryptocurrency analysis.

Use Cases:

Market Analysis: Analyze price trends and historical market behavior of leading cryptocurrencies. Price Prediction: Use the data to build predictive models, such as time-series forecasting for future price movements. Backtesting: Test trading strategies and financial models on historical data. Volatility Analysis: Assess the volatility of top cryptocurrencies to gauge market risk. Overview of the Cryptocurrencies in the Dataset: Bitcoin (BTC): The pioneer cryptocurrency, often referred to as digital gold and used as a store of value. Ethereum (ETH): A decentralized platform for building smart contracts and decentralized applications (DApps). Ripple (XRP): A payment protocol focused on enabling fast and low-cost international transfers. Tether (USDT): A popular stablecoin pegged to the US Dollar, providing price stability for trading and transactions. Solana (SOL): A high-speed blockchain known for low transaction fees and scalability, often seen as a competitor to Ethereum. Binance Coin (BNB): The native token of Binance, the world's largest cryptocurrency exchange, used for various purposes within the Binance ecosystem. Dogecoin (DOGE): Initially a meme-inspired coin, Dogecoin has gained a strong community and mainstream popularity. USD Coin (USDC): A fully-backed stablecoin pegged to the US Dollar, commonly used in decentralized finance (DeFi) applications. Cardano (ADA): A proof-of-stake blockchain focused on scalability, sustainability, and security. Staked Ethereum (STETH): A token representing Ethereum staked in the Ethereum 2.0 network, earning staking rewards.

This dataset provides a comprehensive overview of key cryptocurrencies that have shaped and continue to influence the digital asset market. Whether you're conducting research, building prediction models, or analyzing trends, this dataset is an essential resource for understanding the evolution of cryptocurrencies from 2014 to December 2024.

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.

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 ---

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.

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 ---