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

Marathon Oil reported $166M in Stock for its fiscal quarter ending in September of 2024. Data for Marathon Oil | MRO - Stock including historical, tables and charts were last updated by Trading Economics this last December 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.

How do you decide buy or sell a stock? (MRO Stock Forecast)

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

Non-traditional data signals from social media and employment platforms for MRO stock analysis

Marathon Oil reported $16.48B in Market Capitalization this November of 2024, considering the latest stock price and the number of outstanding shares.Data for Marathon Oil | MRO - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December 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.

Should You Buy Now or Wait? (MRO Stock Forecast)

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

Melrose reported GBP557M in Stock for its fiscal semester ending in June of 2023. Data for Melrose | MRO - Stock including historical, tables and charts were last updated by Trading Economics this last December 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.

How Is Machine Learning Used in Trading? (LON:MRO Stock Forecast)

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

Marathon Oil reported $1.12B in EBITDA for its fiscal quarter ending in September of 2024. Data for Marathon Oil | MRO - Ebitda including historical, tables and charts were last updated by Trading Economics this last December in 2025.

The global MRO (Maintenance, Repair, and Overhaul) Rolling Stock Market is projected to reach a valuation of approximately USD 85 billion by 2033, growing at a compound annual growth rate (CAGR) of 4.5% from 2025 to 2033.

AI-powered price forecasts for MRO.L stock across different timeframes including weekly, monthly, yearly, and multi-year predictions.

Marathon Oil reported $11.44B in Equity Capital and Reserves for its fiscal quarter ending in September of 2024. Data for Marathon Oil | MRO - Equity Capital And Reserves including historical, tables and charts were last updated by Trading Economics this last December in 2025.

MRO Stores Management Market Outlook

As per our latest research, the global MRO Stores Management market size is valued at USD 7.8 billion in 2024, demonstrating a robust foundation for this critical sector. The market is experiencing a healthy expansion with a CAGR of 7.1% from 2025 to 2033. By the end of 2033, the MRO Stores Management market is forecasted to reach USD 14.5 billion. This growth is primarily driven by the increasing adoption of digital solutions for inventory optimization, the rising need for cost efficiency across industries, and the growing complexity of supply chain operations worldwide.

A key growth factor for the MRO Stores Management market is the accelerating digital transformation across industries. Organizations are increasingly leveraging advanced technologies such as IoT, AI-driven analytics, and cloud-based platforms to streamline their maintenance, repair, and operations (MRO) processes. These digital solutions enable real-time inventory tracking, predictive maintenance, and data-driven decision-making, which significantly reduce downtime and operational costs. The integration of smart technologies not only enhances visibility across the supply chain but also improves overall efficiency, making it a compelling value proposition for enterprises seeking to optimize their MRO functions.

Another significant driver is the rising emphasis on cost optimization and regulatory compliance in asset-intensive industries. Sectors such as manufacturing, energy, and aerospace are under constant pressure to maintain high operational efficiency while adhering to stringent safety and quality standards. Effective MRO Stores Management ensures that critical spare parts and consumables are available when needed, minimizing costly production stoppages. Furthermore, robust management systems help organizations comply with industry regulations by providing accurate record-keeping and traceability, which is vital for audits and certifications. This dual advantage of cost savings and regulatory adherence is propelling the adoption of advanced MRO solutions.

The globalization of supply chains and the increasing complexity of asset management are also fueling the demand for comprehensive MRO Stores Management solutions. As companies expand their operations across multiple geographies, managing MRO inventory becomes more challenging due to diverse supplier networks, varying lead times, and fluctuating demand patterns. Integrated MRO platforms offer centralized control and visibility, enabling organizations to standardize processes, negotiate better contracts with suppliers, and optimize inventory levels across locations. This global perspective is particularly important for multinational corporations aiming to achieve consistency and scalability in their MRO strategies.

From a regional standpoint, North America currently holds the largest market share in the MRO Stores Management market, driven by the presence of major manufacturing hubs, advanced technological adoption, and a strong focus on operational excellence. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, fueled by rapid industrialization, infrastructure development, and increasing investments in digital transformation initiatives. Europe also represents a significant market, supported by stringent regulatory frameworks and a mature industrial base. Latin America and the Middle East & Africa are emerging as promising markets, with growing awareness of the benefits of efficient MRO management and increasing adoption among local enterprises.

Solution Analysis

The Solution segment in the MRO Stores Management market encompasses a range of offerings including Inventory Management, Procurement Management, Order Management, Supplier Management, Analytics & Reporting, and others. Inventory Management remains the cornerstone of MRO stores management, as maintaining optimal stock levels is critical for uninterrupted operations. Advanced inventory man

The Digital MRO Market Report is Segmented by Technology (Digital Twin, AR/VR, 3D Printing, Internet of Things (IoT), Blockchain, and More), Application (Inspection and Damage Assessment, Performance Monitoring, Predictive Analysis, Inventory and Part Replacement, and More), End User (Airlines, Independent MROs, and More), and Geography (North America, Europe, and More). The Market Forecasts are Provided in Terms of Value (USD).

The United States Oil and Gas Pipeline Maintenance, Repair, and Overhaul (MRO) Market Report is Segmented by Service Type (Inspection and Monitoring, Maintenance, Overhaul and Replacement, Decommissioning, and More), Pipeline Type (Gathering Lines, Transmission Lines, Distribution Lines), Location of Deployment (Onshore and Offshore), and End-User Sector (Upstream, Midstream Operators, and Downstream and Petrochemicals).

Marathon Oil reported $937M in Ordinary Share Capital for its fiscal quarter ending in September of 2024. Data for Marathon Oil | MRO - Ordinary Share Capital including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Marathon Oil reported $0.64 in EPS Earnings Per Share for its fiscal quarter ending in September of 2024. Data for Marathon Oil | MRO - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Inventory Optimization for Oil and Gas MRO Market Outlook

As per our latest research, the global inventory optimization for oil and gas MRO market size was valued at USD 2.84 billion in 2024. The market is expected to grow at a steady CAGR of 7.1% during the forecast period, reaching a projected value of USD 5.28 billion by 2033. This robust growth is primarily driven by the increasing need for operational efficiency, cost reduction, and digital transformation initiatives within the oil and gas sector, which are prompting companies to adopt advanced inventory optimization solutions for their Maintenance, Repair, and Operations (MRO) processes.

The oil and gas industry is inherently complex, with vast networks of equipment and facilities that require regular maintenance and repair. This complexity often leads to significant challenges in managing spare parts inventories, resulting in excess stock, stockouts, and high carrying costs. The adoption of inventory optimization solutions is being fueled by the industry’s focus on minimizing downtime and ensuring the availability of critical MRO parts. As companies strive to streamline their supply chains and improve asset reliability, advanced analytics and artificial intelligence (AI)-powered inventory management platforms are becoming increasingly vital. These technologies enable predictive maintenance, accurate demand forecasting, and real-time visibility into inventory levels, all of which contribute to substantial cost savings and enhanced operational agility.

Another key growth driver for the inventory optimization for oil and gas MRO market is the growing trend of digitalization. Oil and gas operators are investing heavily in digital technologies to modernize their MRO operations, integrating Internet of Things (IoT) sensors, cloud-based platforms, and machine learning algorithms. These digital tools facilitate seamless data collection and analysis, allowing companies to make informed decisions regarding spare parts procurement, storage, and usage. The push towards Industry 4.0 and the adoption of digital twins further amplify the demand for sophisticated inventory optimization solutions, as these innovations help companies simulate various maintenance scenarios, optimize spare parts allocation, and reduce unnecessary expenditures.

The market’s growth is also being propelled by stringent regulatory requirements and the need for sustainability. Regulatory bodies are imposing stricter guidelines on equipment maintenance, environmental safety, and supply chain transparency. As a result, oil and gas companies are compelled to implement robust MRO inventory management practices to ensure compliance and mitigate risks associated with equipment failures or environmental incidents. Moreover, by optimizing inventories, companies can reduce waste, lower carbon footprints, and support their broader sustainability objectives. The convergence of regulatory compliance and sustainability imperatives is thus driving the widespread adoption of inventory optimization solutions across the oil and gas value chain.

Regionally, North America holds the largest share of the global inventory optimization for oil and gas MRO market, followed by Europe and Asia Pacific. The presence of major oil and gas players, advanced technological infrastructure, and a strong focus on digital transformation contribute to North America’s leading position. Meanwhile, rapid industrialization and increasing investments in oil and gas exploration activities are fueling the market’s expansion in Asia Pacific. The Middle East & Africa region, with its significant oil reserves and ongoing modernization efforts, is also emerging as a lucrative market for inventory optimization solutions. Latin America is witnessing steady growth, driven by the need to enhance operational efficiency and reduce costs in a highly competitive landscape.

Component Analysis

The component segment of the inventory optimization for oil and gas MRO market is bifurcated into software and services. Software solutions form the backbone of inventory optimization, providing oil and gas companies with robust platforms to manage, analyze, and optimize their MRO inventories. These software tools leverage advanced analytics, artificial intelligence, and machine learning algorithms to forecast demand, track inventory levels in real-time, and recommend optimal stock levels. As digital transformation sweeps across the oil

Mro Equipment And Service Joint Stock Company Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The size of the MRO Software market was valued at USD 908.3 million in 2024 and is projected to reach USD 1211.44 million by 2033, with an expected CAGR of 4.2 % during the forecast period.