The beef cattle industry is driven by factors such as demand for meat, changes in consumer preferences, growth in population, and economic conditions. This article discusses how these factors influence the beef cattle stock market and emphasizes the importance of understanding the different segments of the industry for producers, buyers, and investors.

The Global Livestock & Meat Market Report is Segmented by Livestock Activity (Live Animals Trade, Edible Meat, Meat Byproducts, and Livestock Products) and Geography (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa). The Report Offers Market Size and Forecast for the Livestock and Meat Market in Value (USD) and Volume (metric Tons) for all the Above Segments.

Live Cattle rose to 214.29 USd/Lbs on July 3, 2025, up 0.81% from the previous day. Over the past month, Live Cattle's price has fallen 1.90%, but it is still 15.03% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Live Cattle - values, historical data, forecasts and news - updated on July of 2025.

Feeder Cattle rose to 309.71 USd/Lbs on July 3, 2025, up 0.26% from the previous day. Over the past month, Feeder Cattle's price has risen 1.78%, and is up 18.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Feeder Cattle - values, historical data, forecasts and news - updated on July of 2025.

The AI In Livestock Farming Market is estimated to reach USD 2,997.9 Mn by 2033, Riding on a Strong 5.5% CAGR during the forecast period.

Global Smart Livestock Farming market size 2025 was XX Million. Smart Livestock Farming Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

The Global Livestock Monitoring Market Report is Segmented by Animal Type (Cattle, Poultry, Equine, and Others), Component (Hardware, Software, and Services), Application (Feeding Management, Milk Harvesting, Breeding Management, and Others), and Geography (North America, Europe, Asia-Pacific, Middle-East and Africa, and South America). The Report Offers the Market Size in Value Terms (USD) for the Above Segments.

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.

CME feeder cattle futures

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 livestock insurance market size reached USD 3.8 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 6.8 Billion by 2033, exhibiting a growth rate (CAGR) of 6.65% during 2025-2033. The increasing prevalence of various disease outbreaks, rising consumer preferences towards animal-based products, and the growing awareness about the health and well being of animals are some of the major factors propelling the market growth.

Report Attribute	Key Statistics
Base Year	2024
Forecast Years	2025-2033
Historical Years	2019-2024
Market Size in 2024	USD 3.8 Billion
Market Forecast in 2033	USD 6.8 Billion
Market Growth Rate 2025-2033	6.65%

IMARC Group provides an analysis of the key trends in each segment of the global livestock insurance market report, along with forecasts at the global, regional and country levels from 2025-2033. Our report has categorized the market based on coverage, animal type, and distribution channel.

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.

Zoetis' (ZTS) Livestock-Focused Strategy Expected to Yield Positive Results, Analysts Predict.

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 statistic displays the market share of standalone software applications in livestock monitoring and management worldwide in 2016 and 2021, by delivery model market. In 2016, the on-cloud standalone delivery systems held a 63 percent share of the standalone software market for livestock monitoring and management.

This statistic displays the market share of hardware and systems applications in livestock monitoring and management worldwide in 2016 and 2021, by technology. In 2016, sensors held a 51 percent share of the hardware and systems technology segment of the livestock monitoring and management market worldwide.

By 2035, the Livestock Farm Equipment Market is estimated to expand to USD 32.92 Billion, showcasing a robust CAGR of 4.46% between 2025 and 2035, starting from a valuation of USD 20.37 Billion in 2024.

The global animal feed market is valued at USD 605.3 billion in 2025 and is poised to reach USD 1,224.6 billion by 2035.

Attribute	Description
Estimated Industry Size (2025E)	USD 605.3 billion
Projected Industry Value (2035F)	USD 1,224.6 billion
Value-based CAGR (2025 to 2035)	7.3%

Semi-Annual Market Update

Particular	Value CAGR
H1 (2024 to 2034)	6.8%
H2 (2024 to 2034)	7.0%
H1 (2025 to 2035)	7.1%
H2 (2025 to 2035)	7.3%

Country-Wise Insights

Countries	CAGR (2025 to 2035)
USA	6.2%
Germany	6.7%
China	7.9%
Japan	7.3%
India	8.5%

Explore Market Research Intellect's Smart Livestock Market Report, valued at USD 5.2 billion in 2024, with a projected market growth to USD 12.7 billion by 2033, and a CAGR of 10.5% from 2026 to 2033.

The livestock farming technology market size was valued at USD 5.9 billion in 2024 and is projected to reach USD 32.2 billion by the end of 2037, rising at a CAGR of 14% during the forecast period, i.e., 2025-2037. North America is projected to retain a 40% market share from 2025 to 2037, driven by

The global Livestock Identification Market is expected to rise USD 3,459.51 million by 2034 And anticipated to grow at a CAGR of 8.0%.

By 2035, the Smart Livestock Monitoring market is estimated to expand to USD 9.80 Billion, showcasing a robust CAGR of 12.6% between 2025 and 2035, starting from a valuation of USD 2.65 Billion in 2024 and USD 2.98 Billion in 2025

Explore the growth potential of Market Research Intellect's GCC Countries Livestock Monitoring Market Report, valued at USD 150 million in 2024, with a forecasted market size of USD 300 million by 2033, growing at a CAGR of 8.5% from 2026 to 2033.