Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.

GSCI fell to 556.57 Index Points on December 2, 2025, down 0.34% from the previous day. Over the past month, GSCI's price has fallen 0.80%, but it is still 3.06% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. GSCI Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

CRB Index rose to 378.33 Index Points on December 1, 2025, up 0.45% from the previous day. Over the past month, CRB Index's price has fallen 0.80%, but it is still 10.95% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

Browse LSEG's Commodities - Overview , discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivaled data and delivery mechanisms.

Overview

The data refers to Daily prices of various commodities in India like Tomato, Potato, Brinjal, Wheat etc. It has the wholesale maximum price, minimum price and modal price on daily basis. the prices in the dataset refer to the wholesale prices of various commodities per quintal (100 kg) in Indian rupees. The wholesale price is the price at which goods are sold in large quantities to retailers or distributors.

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Features of the dataset include:

• State: The state in India where the market is located.
• District: The district in India where the market is located.
• Market: The name of the market.
• Commodity: The name of the commodity.
• Variety: The variety of the commodity.
• Grade: The grade or quality of the commodity.
• Min Price: (INR) The minimum wholesale price of the commodity on a given day, per quintal (100 kg).
• Max Price: (INR) The maximum wholesale price of the commodity on a given day, per quintal (100 kg).
• Modal Price: (INR) The most common or representative wholesale price of the commodity on a given day, per quintal (100 kg).

1 INR = 0.012 USD (as on 17 August, 2023)

Use Cases

Market analysis: You can use this dataset to analyze trends and patterns in the wholesale prices of various commodities across different markets in India. This can help you understand factors that affect prices, such as supply and demand, seasonality, and market conditions. Commodity recommendation: Develop recommender systems that suggest the best markets or commodities for farmers or traders to sell or buy based on their location, preferences, and market conditions.

Licensed under the Government Open Data License - India (GODL) https://data.gov.in/government-open-data-license-india

Feel free to download the data and use it in your work. I will wait for interesting notebooks from your side. Thank you

Search LSEG's Commodities Data, and find global pricing, exchanges, and fundamentals for energy, agriculture, and metals.

This dataset provides the current daily prices of various commodities sourced from multiple markets (mandis) across different regions. It includes detailed information on the market names, commodity types, and their respective prices, offering a snapshot of real-time agricultural and other commodity market trends. The data is valuable for farmers, traders, and analysts to monitor price fluctuations, compare regional price variations, and make informed decisions. It offers insights into supply and demand dynamics, and market conditions, and helps in understanding the economic factors affecting commodity pricing. This dataset supports decision-making, price forecasting, and market research.

Commodity Price Risk Dashboards Market Outlook

According to our latest research, the global commodity price risk dashboards market size reached USD 1.45 billion in 2024, reflecting the growing importance of real-time risk management tools in volatile commodity markets. With a robust compound annual growth rate (CAGR) of 10.6%, the market is projected to expand to USD 3.62 billion by 2033. This impressive growth is primarily driven by the increasing complexity of global supply chains, heightened geopolitical risks, and the escalating demand for data-driven decision-making across industries.

One of the most significant growth factors fueling the commodity price risk dashboards market is the increasing volatility and unpredictability in global commodity prices. Over the past decade, geopolitical tensions, trade disputes, and climate change events have contributed to sharp fluctuations in the prices of essential commodities such as oil, agricultural products, and metals. Enterprises and financial institutions are under mounting pressure to manage exposure to price risks more efficiently. As a result, organizations are rapidly adopting advanced dashboards that offer real-time price monitoring, predictive analytics, and scenario modeling capabilities. These tools empower stakeholders to make informed decisions, optimize procurement strategies, and safeguard profit margins against unpredictable market swings.

Another key driver is the digital transformation sweeping across industries, particularly in sectors with significant exposure to commodity risks such as energy, agriculture, and manufacturing. The integration of artificial intelligence, machine learning, and big data analytics into commodity price risk dashboards has elevated their value proposition. Modern dashboards can now process vast datasets from multiple sources, offering actionable insights and automated alerts. This technological evolution has not only improved the accuracy of risk assessments but also enhanced the speed at which organizations can respond to market movements. The growing emphasis on automation and data-driven strategies is expected to sustain robust demand for commodity price risk dashboards throughout the forecast period.

Furthermore, stringent regulatory requirements and the growing need for transparency in financial reporting have compelled organizations to adopt sophisticated risk management solutions. Regulatory bodies across the globe are mandating more comprehensive reporting and risk disclosure standards, particularly for companies engaged in commodity trading and procurement. Commodity price risk dashboards facilitate compliance by providing auditable records, detailed analytics, and customizable reporting features. This regulatory push, coupled with the increasing adoption of enterprise risk management frameworks, is anticipated to further stimulate market growth, as organizations seek to align their risk management practices with global standards.

From a regional perspective, North America currently leads the commodity price risk dashboards market, accounting for the largest share in 2024. This dominance is attributed to the presence of major commodity trading hubs, advanced technological infrastructure, and a high concentration of multinational corporations. However, Asia Pacific is poised to exhibit the highest growth rate during the forecast period, driven by rapid industrialization, expanding commodity markets, and increasing investments in digital transformation initiatives. Europe also remains a significant market, supported by robust regulatory frameworks and a strong emphasis on sustainability and risk management in commodity-intensive industries.

Component Analysis

The commodity price risk dashboards market is segmented by component into software and services, each playing a pivotal role in addressing the diverse needs of end-users. Software solutions constitute the core of risk management, offering advanced functionalities such as real-time price tracking, analytics,

Graph and download economic data for Producer Price Index by Commodity: Pulp, Paper, and Allied Products: Wood Pulp (WPU0911) from Jan 1926 to Sep 2025 about wood, paper, commodities, PPI, inflation, price index, indexes, price, and USA.

Historical commodity (daily) price from 2000-2022 (March). 1. Gold 2. Palladium 3. Nickel 4. Brent Oil 5. Natural Gas 6. Wheat

• cover image credit: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

LME Index rose to 4,700 Index Points on October 29, 2025, up 0.79% from the previous day. Over the past month, LME Index's price has risen 7.33%, and is up 13.22% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. LME Index - values, historical data, forecasts and news - updated on December of 2025.

Commodity Price Risk Analytics for SMEs Market Outlook

According to our latest research, the global Commodity Price Risk Analytics for SMEs market size reached USD 1.42 billion in 2024, registering a robust year-on-year growth. The market is expected to expand at a CAGR of 11.7% during the forecast period, reaching approximately USD 4.07 billion by 2033. This growth is primarily driven by the increasing volatility in global commodity prices, which is compelling small and medium enterprises (SMEs) to adopt advanced risk analytics solutions to safeguard their profitability and ensure business continuity.

A significant factor propelling the expansion of the Commodity Price Risk Analytics for SMEs market is the heightened awareness among SMEs regarding the adverse impacts of commodity price fluctuations. With global supply chains becoming increasingly complex and susceptible to geopolitical tensions, natural disasters, and regulatory changes, SMEs are recognizing the necessity for sophisticated analytics tools. These solutions enable businesses to proactively monitor, predict, and hedge against price risks, thereby minimizing financial exposure. The democratization of data analytics and the proliferation of user-friendly platforms have further lowered the entry barriers for SMEs, empowering them to make data-driven decisions that were previously accessible only to larger enterprises.

Another key driver for the market is the rapid digital transformation across all sectors, which has made advanced analytics more accessible and affordable for SMEs. The integration of artificial intelligence, machine learning, and big data analytics into commodity risk management platforms has significantly enhanced predictive accuracy and operational efficiency. These technological advancements allow SMEs to automate complex risk calculations, simulate various market scenarios, and optimize procurement and inventory strategies. As a result, businesses are better equipped to reduce costs, improve margins, and maintain a competitive edge in increasingly volatile markets.

The growing importance of regulatory compliance and transparency in financial reporting is also fueling the demand for commodity price risk analytics among SMEs. Governments and regulatory bodies worldwide are imposing stricter reporting requirements and risk management standards, especially in sectors heavily reliant on commodities such as manufacturing, agriculture, and energy. By leveraging advanced analytics solutions, SMEs can not only ensure compliance but also gain deeper insights into their risk exposures and opportunities. This dual benefit is prompting a surge in adoption rates, particularly among SMEs aiming to scale operations and attract investment by showcasing robust risk management frameworks.

Regionally, North America continues to dominate the Commodity Price Risk Analytics for SMEs market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The strong presence of technology providers, a mature SME ecosystem, and high awareness of risk management best practices contribute to North America’s leadership. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid industrialization, expanding SME sectors, and increasing exposure to global commodity markets. Latin America and the Middle East & Africa are also emerging as important markets, supported by government initiatives to promote digital adoption among SMEs and the rising importance of commodity exports in these regions.

Component Analysis

The Component segment of the Commodity Price Risk Analytics for SMEs market is bifurcated into Software and Services. Software solutions form the backbone of this market by providing SMEs with advanced analytical tools that enable real-time monitoring, price forecasting, and automated reporting. These platforms are increasingly leveraging artificial intelligence and machine learning algorithms to enhanc

Agmarknet India Commodity Prices (October 2024 – August 2025)

🧩 Overview

This dataset contains daily agricultural commodity price data scraped from the Agmarknet (Government of India) portal for the period October 2024 to August 2025.
It provides granular market-level data across multiple states, including information on commodity, variety, grade, and minimum, maximum, and modal prices (in Rs./Quintal).

With over 1.1 million records, this dataset offers valuable insights into agricultural price fluctuations and regional market dynamics in India.

📅 Time Period

October 2024 – August 2025

📊 Dataset Columns Description

🌾 Data Source

Data has been scraped from the official Agmarknet portal maintained by the Directorate of Marketing & Inspection (DMI) under the Ministry of Agriculture and Farmers Welfare, Government of India.
👉 https://agmarknet.gov.in/

📈 Possible Use Cases

• Agricultural price forecasting using machine learning
• Commodity-wise seasonal and regional trend analysis
• Correlation between price volatility and climatic or policy factors
• Decision support for farmers and agri-businesses
• Market intelligence and demand-supply analysis

🧮 Dataset Statistics

• Records: 1,118,899
• Features: 11
• Coverage: 8 Indian states and 1160 markets
• Frequency: Daily

⚖️ License

This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
You are free to use, share, and adapt this dataset for any purpose, provided that you give appropriate credit and share derivatives under the same license.

📢 Citation

If you use this dataset in your research, please cite it as:

Anish (2025). Agmarknet India Commodity Prices (October 2024 – August 2025).
Retrieved from https://agmarknet.gov.in/

🧠 Acknowledgments

Special thanks to the Ministry of Agriculture & Farmers Welfare, Government of India, for maintaining open access to Agmarknet data, which enables valuable research and innovation in agricultural analytics.

Stock and commodity exchanges can benefit from various sources of revenue, ranging from fees charged through the purchasing and selling of stocks and commodities to the listing of companies on exchanges with IPOs. Yet, this hasn't meant exchanges have been free of challenges, with many companies looking to more attractive overseas markets in countries like the US that embrace stronger growth. The most notable culprits have been ARM and CRH, refusing to put up with the increasingly cheaper valuations offered by UK stock exchanges.Stock and commodity exchange revenue is expected to boom at a compound annual rate of 13% over the five years through 2025-26 to £18 billion, including growth of 5.2% in 2025-26. Boosted by the London Stock Exchange Group's Refinitiv purchase in 2021-22, the growth numbers seem inflated. The industry saw ample consolidations, aided by MiFID II's initiation in 2018. However, M&As have slumped over recent years as a result of high borrowing costs and a foggy economic outlook. Interest rate cuts and growing confidence are set to facilitate a modest recovery over the two years through 2025, driving revenue growth and supporting profit of 25.7% in 2025-26. Exchanges have also capitalised on volatile markets, with nervous investors triggering sharp sell-offs amid a tense geopolitical backdrop with Trump’s tariff policies. Consolidation amongst the largest players has been frequent, ratcheting up market share concentration. This will also prompt smaller exchanges to target niche markets and potentially band together in networks or alliances to pool liquidity and strengthen bargaining power. Revenue is forecast to climb at a compound annual rate of 4.7% over the five years through 2030-31 to £22.7 billion. Over the short term, sticky inflation and how aggressively the Bank of England cuts rates will incite volatility and fuel trading on exchanges, driving revenue growth. Geopolitical tensions also show no signs of cooling, with the potential for matters to even escalate, keeping markets edgy and increasing the likelihood of large market swings. The use of blockchain will become more prevalent, with major player, the London Stock Exchange Group, already introducing a blockchain-based infrastructure platform for private markets. These exchanges allow for 24/7 trading, lower settlement times, and often lower fees, which can attract retail and institutional participants, driving fee income.

S&P Global Commodity Insights is the leading independent provider of information, benchmark prices, and analytics for the energy and commodities markets.

Corn rose to 433.53 USd/BU on December 2, 2025, up 0.01% from the previous day. Over the past month, Corn's price has fallen 0.17%, but it is still 2.43% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on December of 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.

Commodity Index: The Future of Investing?

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

Learn about the importance of live grain market prices and how to access up-to-date information on the current prices of different grain commodities through commodity exchanges, news and analysis platforms, and free online price tracking tools.

Orange Juice fell to 147.99 USd/Lbs on December 2, 2025, down 0.38% from the previous day. Over the past month, Orange Juice's price has fallen 15.22%, and is down 71.10% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Orange Juice - values, historical data, forecasts and news - updated on December of 2025.

In 2024, the average price for aluminum stood at 2,419 nominal U.S. dollars per metric ton. This statistic depicts the average annual prices for aluminum from 2014 through 2026.