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.

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.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

Crude Oil fell to 59.17 USD/Bbl on December 2, 2025, down 0.25% from the previous day. Over the past month, Crude Oil's price has fallen 3.08%, and is down 15.40% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on December of 2025.

Real-time quotes for crude oil play a crucial role in the financial and commodities markets. These quotes provide traders, investors, and analysts with up-to-date information about the current price and performance of crude oil. The prices of crude oil are influenced by various factors such as supply and demand, geopolitical events, economic data, and weather conditions.

Real-time commodity prices and currency exchange rates for major global markets

The article explains the concept of real-time oil futures prices and their significance in the energy markets. It discusses the factors that influence these prices and how investors and traders use them to make informed decisions. The availability of real-time oil futures prices and their role in managing exposure to oil price fluctuations are also emphasized.

Learn about the importance of real-time oil futures data for traders and investors, including contract specifications, price quotes, trading volume, open interest, and market trends.

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.

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.

Oil futures live quotes provide real-time price information for oil futures contracts, enabling traders and investors to track and analyze the market. This article explains what oil futures are, how live quotes are structured, and how they can be utilized to make informed trading decisions.

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 balanced annual panel data for 32 sub-Saharan countries from 2000 to 2020 was used for this study. The countries and period of study was informed by availability of data of interest. Specifically, 11 agricultural commodity dependent countries, 7 energy commodity dependent countries and 14 mineral and metal ore dependent countries were selected (Appendix 1). The annual data comprised of agricultural commodity prices, global oil prices (GOP) and mineral and metal ore prices, export value of the dependent commodity, total export value of the country, real GDP (RGDP) and terms of trade (TOT). The data for export value of the dependent commodity, total export value of the country, real GDP and terms of trade was sourced from world bank database (World Development Indicators). Data for agricultural commodity prices, global oil prices (GOP) and mineral and metal ore prices are obtained from World Bank commodity price data portal. This study used data from global commodity prices from the World Bank's commodity price data site since the error term (endogenous) is connected with each country's commodity export price index. The pricing information covered agricultural products, world oil, minerals, and metal ores. One benefit of adopting international commodity prices, according to Deaton and Miller (1995), is that they are frequently unaffected by national activities. The utilization of studies on global commodity prices is an example (Tahar et al., 2021). The commodity dependency index of country i at time i was computed as the as the ratio of export value of the dependent commodity to the total export value of the country. The commodity price volatility is estimated using standard deviation from monthly commodity price index to incorporate monthly price variation (Aghion et al., 2009). This approach addresses challenges of within the year volatility inherent in the annual data. In footstep of Arezki et al. (2014) and Mondal & Khanam (2018), standard deviation is used in this study as a proxy of commodity price volatility. The standard deviation is used because of its simplicity and it is not conditioned on the unit of measurement.

Time series data for the commodity Primary Commodity Prices, Groundnuts . Indicator Definition:Primary Commodity Prices, Groundnuts The indicator "Primary Commodity Prices, Groundnuts " stands at 2.66 Thousand as of 8/31/2025, the highest value since 8/31/2023. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.14 percent compared to the value the year prior.The 1 year change in percent is 6.14.The 3 year change in percent is 10.15.The 5 year change in percent is 37.86.The 10 year change in percent is 30.10.The Serie's long term average value is 1.42 Thousand. It's latest available value, on 8/31/2025, is 87.57 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 5/31/2002, to it's latest available value, on 8/31/2025, is +353.38%.The Serie's change in percent from it's maximum value, on 7/31/2023, to it's latest available value, on 8/31/2025, is -1.65%.

Time series data for the commodity Primary Commodity Prices, Coffee index . Indicator Definition:Primary Commodity Prices, Coffee index The indicator "Primary Commodity Prices, Coffee index " stands at 223.80 as of 8/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 11.39 percent compared to the value the year prior.The 1 year change in percent is 11.39.The 3 year change in percent is 55.61.The 5 year change in percent is 146.61.The 10 year change in percent is 132.43.The Serie's long term average value is 93.49. It's latest available value, on 8/31/2025, is 139.38 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 10/31/2001, to it's latest available value, on 8/31/2025, is +638.31%.The Serie's change in percent from it's maximum value, on 2/28/2025, to it's latest available value, on 8/31/2025, is -18.14%.

Time series data for the commodity Primary Commodity Prices, Vegetables, Tomato. Indicator Definition:Primary Commodity Prices, Vegetables, TomatoThe indicator "Primary Commodity Prices, Vegetables, Tomato" stands at 3.90 as of 08/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 12.86 percent compared to the value the year prior.The 1 year change in percent is 12.86.The 3 year change in percent is 42.51.The 5 year change in percent is 22.99.The 10 year change in percent is 38.59.

REST API access to thousands of currency pairs, cryptocurrencies and commodities. 100,000 requests/day - €50/month. Real-time quotes and max. available history for all cryptos, currencies and commodities!

Commodity Price Range 1877-Present

Historical Futures Contract Pricing for Wheat, Corn, and Oats

By [source]

About this dataset

This dataset contains over 140 years of historical commodity price ranges for wheat, corn, and oats futures contracts. It provides a glimpse into the evolution of our modern economic markets and the constant fluctuations in demand and supply that occur at all times. This data is invaluable to academic researchers, corporate strategists, economists, investors and traders alike as it reveals timely insight into various commodities' pricing trends over time. Each record includes the corresponding highest and lowest prices for each particular well-traded commodity on each particular day since 1877— providing an essential view into market dynamics across multiple decades. Use this data to identify recent pricing patterns or make predictions about future prices – no matter how you decide to use it–this may give you further insight into the ever-changing marketplace

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How to use the dataset

This dataset contains historical commodity price ranges for wheat, corn, and oats futures contracts from 1877 to present. It is a great resource for anyone interested in analyzing the trends of these commodities over time. Each row contains one day's data on the low and high prices of each contract.

To use this dataset, start by looking at the columns. There are several columns to choose from depending on which type of commodity you would like to analyze: Range_W_F1 (Lowest Price of Wheat Futures Contract), Range_W_F2 (Highest Price of Wheat Futures Contract), Range_C_F1 (Lowest Price of Corn Futures Contract), Range_C_F2 (Highest Price of Corn Futures Contract) and Range_O_F1 & 2 (Lowest and Highest Prices respectively for Oats Futures Contracts). Once you have selected the relevant columns for your analysis, pick a date range to focus on and filter out the rows outside that range. This will leave only those days within your chosen timeframe in the dataset so you can begin analyzing them more closely.

For an in-depth analysis it can be helpful to add other pieces data such as weather information or other economic indicators alongside these price ranges so you can investigate possible correlations between different factors that affect pricing in these markets over time. No matter how complex an analysis you might want to do with this data, this dataset provides a good starting point with reliable historical records dating all the way back over 140 years ago!

Research Ideas

• Market analysis to identify trends in prices of different commodities over time.
• Predictive modeling to forecast future prices based on past price ranges and market conditions.
• Proactive risk management strategies by tracking changes in commodity prices and anticipating potential changes in raw material costs for manufacturers or businesses that rely on commodities as part of their production processes

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: rangedata_commodities_since1877.csv | Column name | Description | |:---------------|:---------------------------------------------------------------| | Date | Date of the commodity price range. (Date) | | Range_W_F1 | Lowest price of wheat futures contract for the day. (Numeric) | | Range_W_F2 | Highest price of wheat futures contract for the day. (Numeric) | | Range_C_F1 | Lowest price of corn futures contract for the day. (Numeric) | | Range_C_F2 | Highest price of corn futures contract for the day. (Numeric) | | Range_O_F1 | Lowest price of oats futures contract for the day. (Numeric) | | Range_O_F2 | Highest price of oats futures contract for the day. (Numeric) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Summary of Commodity Price Relationships Across Data Sources.

Content

Gold Futures Historical Data Periode data : Nov 01, 2017 - Oct 16,2020 Source :https://www.investing.com/commodities/gold-historical-data

Disclaimer: According to Fusion Media (https://www.investing.com/commodities/gold-historical-data) that the data contained in their website is not necessarily real-time nor accurate. All CFDs (stocks, indexes, futures), cryptocurrencies, and Forex prices are not provided by exchanges but rather by market makers, and so prices may not be accurate and may differ from the actual market price, meaning prices are indicative and not appropriate for trading purposes.