Meta reported $8.88 in EPS Earnings Per Share for its fiscal quarter ending in December of 2025.Data for Meta | FB - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last March in 2026.

Fb Financial reported $1.16 in EPS Earnings Per Share for its fiscal quarter ending in December of 2025.Data for FB Financial | FBK - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last March in 2026.

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

Meta reported $22.77B in Net Income for its fiscal quarter ending in December of 2025.Data for Meta | FB - Net Income including historical, tables and charts were last updated by Trading Economics this last March in 2026.

Facebook probably needs no introduction; nonetheless, here is a quick history of the company. The world’s biggest and most-famous social network was launched by Mark Zuckerberg while he was a...

Meta reported $24.74B in Operating Profit for its fiscal quarter ending in December of 2025.Data for Meta | FB - Operating Profit including historical, tables and charts were last updated by Trading Economics this last March in 2026.

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.

FB Financial: Riding the Tennessee Wave (FBKstock)

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.

FB Financial Stock: Analysts Predict Growth for (FBK)

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

Meta reported 28.1 in PE Price to Earnings for its fiscal quarter ending in December of 2025.Data for Meta | FB - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last March in 2026.

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.

FB Financial Corp. Stock: Analysts Forecast Upward Trend for (FBK)

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

Advertising accounts for the vast majority of Meta’s revenue. In 2025, it generated over 196 billion U.S. dollars, representing a 22.1 percent increase compared with the previous year. Facebook advertising revenue – additional information Facebook’s business model heavily relies on ads, as the majority of social network’s revenue comes from advertising. In 2020, about 97.9 percent of Facebook's global revenue was generated from advertising, whereas only around two percent was generated by payments and other fees revenue. Facebook ad revenue stood at close to 86 billion U.S. dollars in 2020, a new record for the company and a significant increase in comparison to the previous years. For instance, the social network generated almost seven billion U.S. dollars in ad revenue in 2013, about 10 billion less than the 2015 figure. Facebook's average revenue per user also significantly increased in the same time span, going from 6.81 U.S. dollars in 2013 to 32.03 U.S. dollars in 2020. The U.S. and Canada are important markets for Facebook, considering the average revenue per user (ARPU) in these two countries is far above the global average. Facebook’s ARPU in the U.S. and Canada was 41.41 U.S. dollars in the last quarter of 2019, while the global average was 8.52 U.S. dollars. In Europe, Facebook’s average revenue per user was 13.21 U.S. dollars during the same time period. In terms of segments, mobile is the most promising advertising form for the company. In 2018, Facebook’s mobile advertising revenue already accounted for 92 percent of the social network’s total advertising revenue. Facebook’s mobile advertising revenue grew from an estimate of 13 billion U.S. dollars in 2015 to 50.6 billion U.S. dollars in 2018.

Meta reported $10.91B in Cost of Sales for its fiscal quarter ending in December of 2025.Data for Meta | FB - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last March in 2026.

During an early 2023 survey among marketing leaders from for-profit companies in the United Kingdom, all of the respondents said their company used social media marketing for B2C services for brand awareness and brand-building. The respective share was roughly 95 percent for B2C products.

Meta reported $36.05B in EBITDA for its fiscal quarter ending in December of 2025.Data for Meta | FB - Ebitda including historical, tables and charts were last updated by Trading Economics this last March in 2026.

Meta reported $35.15B in Operating Expenses for its fiscal quarter ending in December of 2025.Data for Meta | FB - Operating Expenses including historical, tables and charts were last updated by Trading Economics this last March in 2026.

Meta reported 67.32K in Employees for its fiscal year ending in December of 2023.Data for Meta | FB - Employees Total Number including historical, tables and charts were last updated by Trading Economics this last March in 2026.

Meta reported $51.06B in Debt for its fiscal quarter ending in September of 2025.Data for Meta | FB - Debt including historical, tables and charts were last updated by Trading Economics this last March in 2026.