Coinbase Global stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Coinbase Global reported $8.23B in Current Liabilities for its fiscal quarter ending in June of 2025. Data for Coinbase Global | COIN - Current Liabilities including historical, tables and charts were last updated by Trading Economics this last September in 2025.

Coinbase Global reported $17.49B in Current Assets for its fiscal quarter ending in June of 2025. Data for Coinbase Global | COIN - Current Assets including historical, tables and charts were last updated by Trading Economics this last September in 2025.

Graph and download economic data for Coinbase Bitcoin (CBBTCUSD) from 2014-12-01 to 2025-09-26 about cryptocurrency and USA.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Coinbase Stock: The Fall of a Crypto Titan?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Coinbase Global reported $1.1 in EPS Earnings Per Share for its fiscal quarter ending in June of 2025. Data for Coinbase Global | COIN - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last September in 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Coinbase Stock: A 5% Drop in the Next 10 Days?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Deze dataset bevat de voorspelde prijzen van Traveling To All 50 States LIVE voor de komende jaren op basis van door de gebruiker gedefinieerde prognoses.

This dataset contains the predicted prices of One Share for the upcoming years based on user-defined projections.

Coinbase Global reported $1.5B in Sales Revenues for its fiscal quarter ending in June of 2025. Data for Coinbase Global | COIN - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last September in 2025.

This dataset contains the predicted prices of First live prison cell till 1m for the upcoming years based on user-defined projections.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Coinbase's Climb: Can it Maintain Momentum? (COIN)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Coinbase: Riding the Crypto Rollercoaster (COIN)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The global user base of cryptocurrencies increased by nearly *** percent between 2018 and 2020, only to accelerate further in 2022. This is according to calculations from various sources, based on information from trading platforms and on-chain wallets. Increasing demographics might initially be attributed to a rise in the number of accounts and improvements in identification. In 2021, however, crypto adoption continued as companies like Tesla and Mastercard announced their interest in cryptocurrency. Consumers in Africa, Asia, and South America were most likely to be owners of cryptocurrencies, such as Bitcoin, in 2022. How many of these users have Bitcoin? User figures for individual cryptocurrencies are unavailable. Bitcoin, for instance, was created not to be tracked by banks and governments. What comes closest is the trading volume of Bitcoin against domestic fiat currencies. The source assumed, however, that UK residents were the most likely to make Bitcoin transactions with British pounds. This assumption might not be accurate for popular fiat currencies worldwide. Moreover, coins such as Tether or Binance Coin - referred to as "stablecoins"—are" often used to buy and sell Bitcoin. Those coins were not included in that particular statistic. Wallet usage declined Total crypto wallet downloads were significantly lower in 2022 than in 2021. The number of downloads of Coinbase, Blockchain.com, and MetaMask, among others, declined as the market hit a "crypto winter" over the year. The crypto market also suffered bad press when FTX, one of the largest crypto exchanges based on market share, collapsed in November 2022. Binance, on the other hand, regained some of the market share it had lost between September and October 2022, growing by *** percentage points in November. As of 2025, the highest forecast for the global user base of cryptocurrencies is projected to reach *** million.

This dataset contains the predicted prices of SHARE for the upcoming years based on user-defined projections.

This dataset contains the predicted prices of Live Ai for the upcoming years based on user-defined projections.

Coinbase Global reported $2.44K in Ordinary Share Capital for its fiscal quarter ending in March of 2025. Data for Coinbase Global | COIN - Ordinary Share Capital including historical, tables and charts were last updated by Trading Economics this last September in 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Coinbase: A Long-Term Investment with Short-Term Volatility

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Ethereum's price history suggests that that crypto was worth more in 2025 than during late 2021, although nowhere near the highest price recorded. Much like Bitcoin (BTC), the price of ETH went up in 2021 but for different reasons altogether: Ethereum, for instance, hit the news when a digital art piece was sold as the world's most expensive NFT for over 38,000 ETH - or 69.3 million U.S. dollars. Unlike Bitcoin, of which the price growth was fueled by the IPO of the U.S.'s biggest crypto trader, Coinbase, the rally on Ethereum came from technological developments that caused much excitement among traders. First, the so-called 'Berlin update' rolled out on the Ethereum network in April 2021, an update that would eventually lead to the Ethereum Merge in 2022 and reduced ETH gas prices - or reduced transaction fees. The collapse of FTX in late 2022, however, changed much for the cryptocurrency. As of August 27, 2025, Ethereum was worth 4,602.37 U.S. dollars - significantly less than the 4,400 U.S. dollars by the end of 2021.Ethereum's future and the DeFi industryPrice developments on Ethereum are difficult to predict but cannot be seen without the world of DeFi, or decentralized finance. This industry used technology to remove intermediaries between parties in a financial transaction. One example includes crypto wallets such as Coinbase Wallet that grew in popularity recently, with other examples including smart contractor Uniswap, Maker (responsible for stablecoin DAI), moneylender Dharma and market protocol Compound. Ethereum's future developments are tied with this industry: Unlike Bitcoin and Ripple, Ethereum is technically not a currency but an open-source software platform for blockchain applications, with Ether being the cryptocurrency that is used inside the Ethereum network. Essentially, Ethereum facilitates DeFi, meaning that if DeFi does well, so does Ethereum.NFTs: the most well-known application of EthereumNFTs or non-fungible tokens, grew nearly tenfold between 2018 and 2020, as can be seen in the market cap of NFTs worldwide. These digital blockchain assets can essentially function as a unique code connected to a digital file, allowing to distinguish the original file from any potential copies. This application is especially prominent in crypto art, although there are other applications: gaming, sports, and collectibles are other segments where NFT sales occur.

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.