Natural gas rose to 4.94 USD/MMBtu on December 3, 2025, up 2.04% from the previous day. Over the past month, Natural gas's price has risen 13.71%, and is up 62.29% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on December of 2025.

The World Bank’s Commodity Markets Outlook is published quarterly, in January, April, July and October. The report provides detailed market analysis for major commodity groups, including energy, metals, agriculture, precious metals and fertilizers. Price forecasts to 2025 for 46 commodities are presented along with historical price data. For more information, please visit: http://www.worldbank.org/commodities For current and past data on Commodity Price Forecasts, please see the Archives data tab on the website.

Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - 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.

United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data was reported at 5.081 % in Apr 2025. This records a decrease from the previous number of 5.233 % for Mar 2025. United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data is updated monthly, averaging 5.027 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 9.843 % in Mar 2022 and a record low of 3.766 % in Nov 2024. United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H080: Survey of Consumer Expectations: Commodity Price.

As an essential part of daily life, the drastic fluctuations in agricultural commodity prices significantly impact producers’ motivation and consumers’ quality of life, further exacerbating market uncertainty and unsustainability. The ability to scientifically and effectively predict agricultural commodity prices is of great significance for the rational deployment of market mechanisms, the timely adjustment of supply chains, and the promotion of food policy adjustments. This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. This innovative approach first performs seasonal decomposition of the original data using the STL method, then applies the VMD method for double decomposition of the residual components, reconstructs the data based on sample entropy, and finally predicts agricultural commodity market prices using the BiLSTM network model optimized by the PSO algorithm. This paper investigates the market price dynamics of four agricultural commodities (chili, garlic, ginger, and pork) and one agricultural financial derivative (soybean futures). The experimental results indicate that the proposed SV-PSO-BiLSTM hybrid model achieves average values of 0.2241 for root mean square error (RMSE), 0.1665 for mean absolute error (MAE), 0.0207 for mean absolute percentage error (MAPE), and 0.9851 for the coefficient of determination (R2). These results surpass those of other comparative models, demonstrating stronger generalization, reliability, and stability. The research findings can provide effective guidance for the reasonable regulation of agricultural commodity market prices and further promote the healthy and sustainable development of the agricultural commodity industry.

The global energy price index stood at around 101.5 in 2024. Energy prices were on a decreasing trend that year, and forecasts suggest the price index would decrease below 80 by 2026. Price indices show the development of prices for goods or services over time relative to a base year. Commodity prices may be dependent on various factors, from supply and demand to overall economic growth. Electricity prices around the world As with overall fuel prices, electricity costs for end users are dependent on power infrastructure, technology type, domestic production, and governmental levies and taxes. Generally, electricity prices are lower in countries with great coal and gas resources, as those have historically been the main sources for electricity generation. This is one of the reasons why electricity prices are lowest in resource-rich countries such as Iran, Qatar, and Russia. Meanwhile, many European governments that have introduced renewable surcharges to support the deployment of solar and wind power and are at the same time dependent on fossil fuel imports, have the highest household electricity prices. Benchmark oil prices One of the commodities found within the energy market is oil. Oil is the main raw material for all common motor fuels, from gasoline to kerosene. In resource-poor and remote regions such as the United States' states of Alaska and Hawaii, or the European country of Cyprus, it is also one of the largest sources for electricity generation. Benchmark oil prices such as Europe’s Brent, the U.S.' WTI, or the OPEC basket are often used as indicators for the overall energy price development.

China Imports Price Index: Commodity data was reported at 1.949 Index, 2015 in 2025. This records an increase from the previous number of 1.941 Index, 2015 for 2024. China Imports Price Index: Commodity data is updated yearly, averaging 1.041 Index, 2015 from Dec 1988 (Median) to 2025, with 38 observations. The data reached an all-time high of 2.007 Index, 2015 in 2022 and a record low of 0.258 Index, 2015 in 1988. China Imports Price Index: Commodity data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.EO: Exports and Imports Price Index: Forecast: Non OECD Member: Annual. PMNW - Price of commodity importsIndex, OECD reference year OECD calculation, see OECD Economic Outlook database documentation

This dataset contains several daily features of NASDAQ Composite, Dow Jones Industrial Average, and NYSE Composite from 2010 to 2024. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables" published at Expert Systems with Applications. This dataset has been used in "SAMBA: A Graph-Mamba Approach for Stock Price Prediction" published at ICASSP 2025. Link to Code: https://github.com/Ali-Meh619/SAMBA

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.

Philadelphia Gold and Silver Index: A Beacon of Precious Metal Value?

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.

DJ Commodity Lead Index Projected to Experience Moderate Growth

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

United States EIA Projection: PPI: Metals & Metal Products data was reported at 2.532 1982=1 in 2050. This records an increase from the previous number of 2.528 1982=1 for 2049. United States EIA Projection: PPI: Metals & Metal Products data is updated yearly, averaging 2.405 1982=1 from Dec 2015 (Median) to 2050, with 36 observations. The data reached an all-time high of 2.532 1982=1 in 2050 and a record low of 1.943 1982=1 in 2016. United States EIA Projection: PPI: Metals & Metal Products data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s USA – Table US.I018: Producer Price Index: By Commodities: Projection: Energy Information Administration.

Gasoline fell to 1.86 USD/Gal on December 2, 2025, down 0.53% from the previous day. Over the past month, Gasoline's price has fallen 2.79%, and is down 4.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - values, historical data, forecasts and news - updated on December of 2025.

Discover the booming global commodity services market, projected to reach $5.9 billion by 2033 with a 5.5% CAGR. This in-depth analysis reveals key drivers, trends, restraints, and top players like Vitol and Glencore, shaping the future of commodity trading.

This dataset contains the predicted prices of the asset Pure Market over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Imports Shadow Price Index: Non-Commodity Goods and Services data was reported at 1.135 Index, 2021 in 2026. This records an increase from the previous number of 1.095 Index, 2021 for 2025. Imports Shadow Price Index: Non-Commodity Goods and Services data is updated yearly, averaging 0.666 Index, 2021 from Dec 1995 (Median) to 2026, with 32 observations. The data reached an all-time high of 1.135 Index, 2021 in 2026 and a record low of 0.163 Index, 2021 in 1995. Imports Shadow Price Index: Non-Commodity Goods and Services data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Indonesia – Table ID.OECD.EO: Exports and Imports Price Index: Forecast: Non OECD Member: Annual.

The size of the Automotive Aluminum Market was valued at USD 10.45 Billion in 2023 and is projected to reach USD 24.28 Billion by 2032, with an expected CAGR of 12.80% during the forecast period. Recent developments include: February 2024: Vedanta Aluminium has come up with Vedanta Metal Bazaar, an e-superstore for primary aluminum that will revolutionize the buying and selling of aluminum in India., The emporium launched with over 750 product variations from Vedanta Aluminium. AI-based pricing discovery gives clients unrivaled value even when commodity prices fluctuate. Ingots, billets, PFA, wire rods, rolled products, flip coils, hot metal, and Restora (India's first low-carbon aluminum) are available. The superstore additionally customizes solutions for its large consumer base., Aluminium is used in aerospace, automotive, building and construction, energy distribution, defense, and other industries. It is called the ‘metal of the future’ because it is essential to the global energy transition, renewable energy, electric vehicles, green infrastructure, and high-tech manufacturing. However, procuring aluminum was formerly complicated and resource-intensive., Vedanta Aluminium created Vedanta Metal Bazaar, a revolutionary e-commerce platform that would change aluminium purchase, to simplify business for customers., It promises to streamline the procurement process, allowing buyers to focus on business growth rather than transactional follow-ups and commodity price and order fulfillment fluctuations. After steel, aluminium is the second most consumed metal worldwide., Buyers may get just-in-time delivery, real-time AI-based pricing discovery, and full visibility from order placement to delivery with Vedanta Metal Bazaar. This enables robust production planning and frees up resources for important expenditures. In a few clicks, clients may use order history, dynamic market circumstances, and competitive rates to make smart purchases., A groundbreaking new platform, Vedanta Metal Bazaar was developed from the ground up to meet consumer expectations and revolutionize the experience., The platform offers global-first features like product availability, online price discovery, long-term contracts, on-the-spot orders, live shipment tracking, financial reconciliation, all critical documentation (such as test certificates, bank guarantees, letters of credit), and a selection of channel finance and logistics providers to help customers procure., September 2022: Alcoa Corporation announced new innovations in alloy development and deployment, further strengthening its position as a supplier of advanced aluminum alloys., May 2022: Novelis Inc. announced it will invest $2.5 billion to build a new low-carbon recycling and rolling plant.. Key drivers for this market are: . Restraints, . Opportunities; . Challenges; . Trends. Potential restraints include: . Opportunities, . Challenges; . Trends. Notable trends are: Growing in the sales and production of several automobiles to boost market growth.

View monthly updates and historical trends for US One-Year Ahead Commodity Price Change Expectations - Gold. from United States. Source: Federal Reserve B…

Monthly and long-term aluminium price data (US$/mt): historical series and analyst forecasts curated by FocusEconomics.