It is estimated that the cumulative market cap of cryptocurrencies increased in early 2023 after the downfall in November 2022 due to FTX. That value declined in the summer of 2023, however, as international uncertainty grew over a potential recession. Bitcoin's market cap comprised the majority of the overall market capitalization. What is market cap? Market capitalization is a financial measure typically used for publicly traded firms, computed by multiplying the share price by the number of outstanding shares. However, cryptocurrency analysts calculate it as the price of the virtual currencies times the number of coins in the market. This gives cryptocurrency investors an idea of the overall market size, and watching the evolution of the measure tells how much money is flowing in or out of each cryptocurrency. Cryptocurrency as an investment The price of Bitcoin has been erratic, and most other cryptocurrencies follow its larger price swings. This volatility attracts investors who hope to buy when the price is low and sell at its peak, turning a profit. However, this does little for price stability. As such, few firms accept payment in cryptocurrencies. As of June 25, 2025, the cumulative market cap of cryptocurrencies reached a value of ******.

How many cryptocurrencies are there? In short, there were over ***** as of August 2025, although there were many more digital coins in the early months of 2022. Note, however, that a large portion of cryptocurrencies might not be that significant. There are other estimates of roughly ****** cryptocurrencies existing, but most of these are either inactive or discontinued. Due to how open the creation process of a cryptocurrency is, it is relatively easy to make one. Indeed, the top 20 cryptocurrencies make up nearly ** percent of the total market. Why are there thousands of cryptocurrencies? Any private individual or company that knows how to write a program on a blockchain can technically create a cryptocurrency. That blockchain can be an existing one. Ethereum and Binance Smart Chain are popular blockchain platforms for such ends, including smart contracts within Decentralized Finance (DeFi). The ease of crypto creation allows some individuals to find solutions to real-world payment problems while others hope to make a quick profit. This explains why some crypto lack utility. Meme coins such as Dogecoin - named after a Japanese dog species - are an infamous example, with Dogecoin's creator coming out and stating the coin started as a joke. The many types of cryptocurrency Meme coins are but one group of cryptocurrencies. Other types include altcoins, utility tokens, governance tokens, and stablecoins. Altcoins are often measured against Bitcoin, as this refers to all crypto that followed Bitcoin - the first digital currency ever created. Utility tokens and governance tokens are somewhat connected to NFTs and the metaverse. A specific example is the MANA cryptocurrency, which allows real estate purchases in the Decentraland metaverse. Stablecoins refer to the likes of Tether, which are pegged to a real-world asset like the U.S. dollar. Such coins are meant to be less volatile than regular cryptocurrency.

Introduction

Cryptocurrency Statistics: Cryptocurrency has lasted for almost a decade, and it is getting bigger and bigger as the days pass. Whereas very few people have knowledge related to the world of crypto trading, it is now a very common thing. More people are joining the team of people who invest in cryptocurrency to make huge money. Nowadays, cryptocurrency has become the most commonly used and accepted asset.

The growing diverse set of individuals investing in cryptocurrency is a major aspect of its success. Even though these cryptocurrencies give unparalleled returns on investment, there are very few rules as of now. Let’s shed more light on the Cryptocurrency Statistics.

Investment cannot be separated from the level of return and risk inherent in assets. Today, investment instruments are not only stocks, currencies, bonds, deposits, savings and others. The beginning of Bitcoin’s emergence as a pioneer of Cryptocurrency was in 2009. Crypto assets are emerging rapidly and are accompanied by an increase in the number of transactions each period. The growth in the market capitalization value of crypto assets has also grown significantly. During COVID-19, many investments, such as stocks, experienced a decline due to market uncertainty. The results of this study prove that with the existence of COVID-19, the crypto market is not affected. Crypto is an attraction characterized by a high degree of fluctuation, and there is no limit to transactions in the open market 24 hours to trade. The Cryptocurrency market is currently a market that can provide short-term benefits to risk-taking investors, while the market in other investment instruments is declining. 78% of the value capitalization of the top 200 cryptocurrencies is represented by the top 9 cryptos used as samples in this study. So that if there is a decrease in these 9 cryptos, it will also have an impact on the overall capitalization value of crypto in the market. The future development of Cryptocurrencies will no longer be digital assets traded with many speculators who can control prices, it can even be digital money that can be used worldwide without any transaction fees and is controlled on a blockchain system. (2023-01-12)

About this dataset As cryptocurrency markets have gained prominence, individuals and organizations have shown an increased fascination with crafting automated trading strategies. The creation of algorithmic trading approaches, though, necessitates rigorous backtesting to ascertain their profitability. Consequently, the cornerstone of any triumphant algorithmic trading strategy lies in the availability of meticulously detailed historical trading data. This dataset will provide you a deeper understanding of working with this type of financial security, it provides you with open, high, low, close (OHLC) information, recorded at 1-hour intervals (not very high-velocity data), encompassing a multitude of cryptocurrency pairs. This data resource is invaluable for those seeking to devise and refine automated trading systems, data analysis, or predictions.

Content This dataset contains the historical trading data (OHLC) of 14 crypto securities at 1 1-hour resolution. The source of this data is Coindesk. The data in the CSV files is refined and cleaned for easier interpretation.

The data is free to use.

At the end of July 2025, the Ethereum cryptocurrency had been processed nearly ** million times on-chain that month. This was about ***** times that of the more commonly known rival Bitcoin, which saw a total of **** million transactions that month. Other leading cryptocurrencies also saw significantly less transaction activity. What kind of transactions were these? Cryptocurrencies are digital currencies which owe their credibility to their technology rather than a central bank. Many of the transactions in this statistic involve cryptocurrency exchanges which exchange these coins for other currencies, including traditional currencies such as U.S. dollars or euros. In selected countries, Bitcoin ATMs also dispense the local currency in exchange for Bitcoin. However, few retailers accept that or any other cryptocurrency on a large scale. Cryptocurrency as an investment Many cryptocurrency enthusiasts point to the high market capitalization of their favorite cryptocurrencies. Moreover, the currency price is an important factor. The price volatility of Bitcoin and others attracts investors, hoping to buy low and sell high.

View daily updates and historical trends for Bitcoin Market Cap. Source: Blockchain.com. Track economic data with YCharts analytics.

Introduction

Digital Currency Statistics: Digital currency, also known as cryptocurrency, is a type of virtual money based on blockchain technology.

Offering decentralization, cryptographic security, and various forms like cryptocurrencies (e.g., Bitcoin, Ethereum).

Central bank digital currencies (CBDCs), stablecoins, and tokenized assets. Transactions are secured through cryptography, and ownership is verified using private and public keys.

Digital currencies have use cases in online transactions, remittances, and investments. Cross-border transfers are characterized by price volatility and face regulatory scrutiny. They rely on consensus mechanisms like mining or proof-of-stake for transaction validation.

Despite challenges, they continue to innovate, attracting investment and reshaping the financial landscape with applications like decentralized finance (DeFi) and non-fungible tokens (NFTs) while undergoing varying degrees of global adoption.

https://scoop.market.us/wp-content/uploads/2023/11/Digital-Currency-Statistics.png" alt="Digital Currency Statistics" class="wp-image-39886">

Historically, gold and silver have played distinct roles in traditional monetary systems. While gold has primarily been revered as a superior store of value, prompting individuals to hoard it, silver has commonly been used as a medium of exchange. As the financial world evolves, the emergence of cryptocurrencies has introduced a new paradigm of value and exchange. However, the store-of-value characteristic of these digital assets remains largely uncharted. Charlie Lee, the founder of Litecoin, once likened Bitcoin to gold and Litecoin to silver. To validate this analogy, our study employs several metrics, including UTXO, STXO, WAL, CoinDaysDestroyed (CDD), and public on-chain transaction data. Furthermore, we've devised trading strategies centered around the Price-to-Utility (PU) ratio, offering a fresh perspective on crypto-asset valuation beyond traditional utilities. Our back-testing results not only display trading indicators for both Bitcoin and Litecoin but also substantiate Lee's metaphor, underscoring Bitcoin's superior store-of-value proposition relative to Litecoin. We anticipate that our findings will drive further exploration into the valuation of crypto assets. For enhanced transparency and to promote future research, we've made our datasets available on Harvard Dataverse and shared our Python code on GitHub as open source.

A league table of the 120 cryptocurrencies with the highest market cap reveals how diverse each crypto is and potentially how much risk is involved when investing in one. Bitcoin (BTC), for instance, had a so-called "high cap" - a market cap worth more than ** billion U.S. dollars - indicating this crypto project has a certain track record or, at the very least, is considered a major player in the cryptocurrency space. This is different in Decentralize Finance (DeFi), where Bitcoin is only a relatively new player. A concentrated market The number of existing cryptocurrencies is several thousands, even if most have a limited significance. Indeed, Bitcoin and Ethereum account for nearly ** percent of the entire crypto market capitalization. As crypto is relatively easy to create, the range of projects varies significantly - from improving payments to solving real-world issues, but also meme coins and more speculative investments. Crypto is not considered a payment method While often talked about as an investment vehicle, cryptocurrencies have not yet established a clear use case in day-to-day life. Central bankers found that usefulness of crypto in domestic payments or remittances to be negligible. A forecast for the world's main online payment methods took a similar stance: It predicts that cryptocurrency would only take up *** percent of total transaction value by 2027.

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.

Reddit: /r/CryptoCurrency

Posts, Scores, Comment Counts and Creation Timestamps

By Reddit [source]

About this dataset

This dataset contains detailed information on posts, scores and comments from the Reddit subreddit ‘CryptoCurrency’ - a fascinating online community devoted to discussion and analysis of the latest developments in blockchain investments, digital currencies, and other associated topics. Dive into the data to see what ultimate insights cryptocurrency enthusiasts are offering each other - their post titles, scores (the net upvotes a post has received), comment counts, created dates and timestamps are all laid out here for easy exploration. By taking advantage of this unique snapshot into crypto discussions and trends you can gain a better understanding not only of what topics have been popular over time but also how they're being discussed across this passionate community. Are there particular trends or patterns that emerge? It's up to you to uncover them!

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How to use the dataset

This dataset contains posts and comments from the subreddit ‘CryptoCurrency’, which is a widely-followed discussion board devoted to discussing cryptocurrencies, blockchain investments, and other related topics. The dataset contains a large number of posts from the subreddit and their associated scores, comment counts and creation timestamps. This dataset can be used in numerous ways for both research and practical business applications.
First, let's explore what columns are contained within this dataset: title, score, url, comms_num (number of comments), created (date and time post was created), body (actual content of the post), timestamp. With this information at hand you can begin answering key questions such as: What type of topics bring more attention? What topics are not popular? Are there any correlations between posts with higher scores(upvotes) or more comments?
To better understand these questions there are numerous tools that can be employed on this data including Natural Language Processing tools such as TF-IDF vectorizers or Latent Dirichlet Allocation to understand what type of themes dominate these conversations. Additionally machine learning algorithms such as clustering techniques like K Nearest Neighbors or Unsupervised Learning techniques like Principal Component Analysis could help uncover insights from this data set. For example if we wanted to find out which words in titles correlated with higher scores then KNN could give us a better understanding as it would build clusters based on similar titles/words and show how each vary in relation score wise giving us an overview on how related words influence scores before analyzing content or any other factors within the data set.
Furthermore Reddit users actively engage with posts so by looking at comment counts insight can also be taken into effect regarding popularity etc... For example one may observe that whenever new coin values arise they tend to have more comments than usual - an insight indicating high levels of user engagement at certain moments in time when compared to regular periods which could be useful when making comparisons between individual coins etc..
Overall this data can provide tremendous value depending on its usage case - whether it stands for research purposes only or applied analytics geared towards predicting prices/engagement/ user sentiment etc it all depends but nonetheless opportunities lie within unlocking financial opportunities through cryptocurrency discussion found on reddit thus making it highly valuable for multiple purposes utilized properly!

Research Ideas

• This dataset can be used to create a sentiment analysis of the comments and posts on CryptoCurrency topics and how these conversations have changed over time. This can help ascertain how different events within the crypto market have been received by investors, speculators, and other users on the subreddit.
• The dataset can also be utilized to identify trends in successful topics of conversation (in terms of post scores) and give insight into what types of topics are popular among Redditors in the CryptoCurrency space.
• Furthermore, this dataset could provide insight into user behavior on CryptoCurrency subreddits by enabling analysis around peak times for certain conversations or post popularity as well as which users tend to comment or post more frequently in response times vs others

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

...

The Cryptocurrency Market Report Segments the Industry by Transaction Purpose (Payments & Remittances, Trading and Investment Transfers, Decentralized Finance (DeFi) Protocol Flows, and More), by User Type (Retail and Institutional), by Cryptocurrency (BTC, ETH, Ripple, and More), and by Geography (North America, South America, Europe, and More). The Crypto Market Forecasts are Provided in Terms of Value (USD).

The appendix contains the list of academic journals from which the articles used in the analysis were taken. It also contains a table showing the contribution of Most Debated Topics to the construction of the axes in Figure 3.

Authors, through Twitter API, collected this database over eight months. These data are tweets of over 50 experts regarding market analysis of 40 cryptocurrencies. These experts are known as influencers on social networks such as Twitter. The theory of Behavioral economics shows that the opinions of people, especially experts, can impact the stock market trend (here, cryptocurrencies). Existing databases often cover tweets related to one or more cryptocurrencies. Also, in these databases, no attention is paid to the user's expertise, and most of the data is extracted using hashtags. Failure to pay attention to the user's expertise causes the irrelevant volume to increase and the neutral polarity to increase considerably. This database has a main table named "Tweets1" with 11 columns and 40 tables to separate comments related to each cryptocurrency. The columns of the main table and the cryptocurrency tables are explained in the attached document. Researchers can use this dataset in various machine learning tasks, such as sentiment analysis and deep transfer learning with sentiment analysis. Also, this data can be used to check the impact of influencers' opinions on the cryptocurrency market trend. The use of this database is allowed by mentioning the source. Also, in this version, we have added the excel version of the database and Python code to extract the names of influencers and tweets. in Version(3): In the new version, three datasets related to historical prices and sentiments related to Bitcoin, Ethereum, and Binance have been added as Excel files from January 1, 2023, to June 12, 2023. Also, two datasets of 52 influential tweets in cryptocurrencies have been published, along with the score and polarity of sentiments regarding more than 300 cryptocurrencies from February 2021 to June 2023. Also, two Python codes related to the sentiment analysis algorithm of tweets with Python have been published. This algorithm combines RoBERTa pre-trained deep neural network and BiGRU deep neural network with an attention layer (see code Preprocessing_and_sentiment_analysis with python).

Live crypto market data on Ju.com, including token prices, market caps, trading volumes, and 24-hour price changes.

This dataset contains the latest market data of the top 1000 cryptocurrencies, including:

• Coin Names and Symbols
• Current Prices (USD)
• Market Capitalization
• 24-hour Price Changes (%)
• Trading Volume
• Last Updated Timestamps

Data was collected in April 2025.

View daily updates and historical trends for Bitcoin Transactions Per Day. Source: Blockchain.com. Track economic data with YCharts analytics.

Global cryptocurrency market valued at USD 3.4 trillion, driven by blockchain adoption, DeFi growth, and institutional investments. Projected to expand with regulatory advancements and CBDCs.

The AWS Public Blockchain Data initiative provides free access to blockchain datasets through collaboration with data providers. The data is optimized for analytics by being transformed into compressed Parquet files, partitioned by date for efficient querying.

Datasets

Blockchain dataset - Maintained by - Path:
- Bitcoin - AWS - s3://aws-public-blockchain/v1.0/btc/
- Ethereum - AWS - s3://aws-public-blockchain/v1.0/eth/
- Arbitrum - SonarX - s3://aws-public-blockchain/v1.1/sonarx/arbitrum/
- Aptos - SonarX - s3://aws-public-blockchain/v1.1/sonarx/aptos/
- Base - SonarX - s3://aws-public-blockchain/v1.1/sonarx/base/
- Provenance - SonarX - s3://aws-public-blockchain/v1.1/sonarx/provenance/
- XRP Ledger - SonarX - s3://aws-public-blockchain/v1.1/sonarx/xrp/
- Stellar(XDR files) - Stellar - s3://aws-public-blockchain/v1.1/stellar/
- The Open Network (TON) - TON - s3://aws-public-blockchain/v1.1/ton/

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