Gold rose to 4,533.64 USD/t.oz on March 27, 2026, up 3.51% from the previous day. Over the past month, Gold's price has fallen 14.82%, but it is still 46.99% higher than a year ago, 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 March of 2026.

Dataset Card for Sentiment Analysis of Commodity News (Gold)

This is a news dataset for the commodity market which has been manually annotated for 10,000+ news headlines across multiple dimensions into various classes. The dataset has been sampled from a period of 20+ years (2000-2021). The dataset was curated by Ankur Sinha and Tanmay Khandait and is detailed in their paper "Impact of News on the Commodity Market: Dataset and Results." It is currently published by the authors on… See the full description on the dataset page: https://huggingface.co/datasets/SaguaroCapital/sentiment-analysis-in-commodity-market-gold.

Gold is a primary global commodity used as a hedge against inflation and currency devaluation. This dataset combines long-term historical benchmarks from the World Bank with recent high-frequency market data to provide a continuous view of gold prices from 1995 through early 2026.

Content

The dataset consists of a single CSV file containing:

Date: The timestamp for the observation (Daily or Monthly).

Gold_Price_USD_YF: Market closing price in USD (via Yahoo Finance).

Gold_Price_WB_Monthly: Global benchmark price per troy ounce (via World Bank).

Data Sources

World Bank (wbdata): Historical global commodity "Pink Sheet" data.

Yahoo Finance (yfinance): Daily market spot and futures prices (Ticker: GC=F). https://finance.yahoo.com/quote/GC=F/history/

License

Data Files (CC BY 4.0): You are free to share and adapt this data as long as credit is given to the original sources (World Bank and Yahoo Finance).

Column Metadata

Assigning descriptions to individual columns is critical for a 10.0 usability score. | Column Name | Description | | :--- | :--- | | Date | The date of record in YYYY-MM-DD format. | | Gold_Price_USD_YF | The daily/monthly average closing price of Gold Futures in USD. | | Gold_Price_WB_Monthly | The monthly global average price of gold per troy ounce (World Bank benchmark). |

Dataset Citations:

World Bank (Primary source for 1995-2000): https://www.worldbank.org/en/research/commodity-markets

Yahoo Finance (Primary source for 2000-2026): https://finance.yahoo.com/quote/GC=F/history

Eurostat (Economic Indicators): https://ec.europa.eu/eurostat/data/database

FAOSTAT (Price Indices): https://www.fao.org/faostat/en/#data/PP

Keywords & Tags:

Finance, Commodities, Economics, Time Series Analysis, Global, Gold Prices, Historical Gold Prices, Monthly Gold Prices, World Bank, Yahoo Finance

Gold prices in , February, 2026 For that commodity indicator, we provide data from January 1960 to February 2026. The average value during that period was 635.09 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 5019.97 USD per troy ounce in February 2026. | TheGlobalEconomy.com

This Dataset contains Historical Price of Gold in Indian Commodity Market . The data has been collected from https://in.investing.com/commodities/ using web scrapping . The script can be customized to suit the needs (like customizing frequency interval , commodity type etc ) Link to web scrapping script - https://github.com/Pritam3355/web_scrapping/blob/master/stock_price.py

Column contains - Date, Price ,Open , High ,Low ,Volume ,Chg% these columns can be sorted first in the website then use the url in script to download the data according to your need

Graph and download economic data for Producer Price Index by Commodity: Metals and Metal Products: Gold Ores (WPU10210501) from Jun 1985 to Dec 2021 about ore, gold, metals, commodities, PPI, inflation, price index, indexes, price, and USA.

The purpose of this study was to look at the cointegration, spillover impact, and lead-lag connection for returns across spot price and the futures price of products gold and silver. Everyday spot and futures prices of Gold and Silver, which were heavily exchanged on the Multi Commodity Exchange (MCX) throughout 2019-2020, were used to compile the data for this study. The return series are considered for testing the spillover effect between the series through GARCH (1,1) Model. The series are checked for stationarity before using the GARCH (1,1) model. The ADF (Augmented Dickey Fuller) test was used to examine the return series' stationarity. The Johansen cointegration and Granger causality tests were used to validating the cointegration and lead-lag connection between futures and spot pricing for chosen bullion commodities after the return series was confirmed stationary. The analysis helps to achieve the following Hypotheses: H01: There is no stationarity in the dataset for the chosen bullion commodities. H02: Cointegration between futures and spot prices is not present in the market for the chosen bullion commodities. H03: The futures price is not influenced by the spot price for the chosen bullion commodities. H04: The Spot price is not influenced by the Futures price for the chosen bullion commodities

The finding provides a new view of the series cointegration, lead-lag, and spillover effect. The spot and futures prices of gold and silver are considered for price discovery. It tells derivatives traders that gold and silver are preferable assets for hedgers and speculators to diversify their portfolios.

In 2024, the rate of return on gold was 26.62 percent, making gold the leading commodity based on return rate in that year. Natural resources, like any other investment, exhibit a wide range of fluctuations over time.

As of December 1st, 2025, gold futures contracts to be settled in June 2031 were trading on U.S. markets at around ***** U.S. dollars per troy ounce. This is above the price of ******* U.S. dollars per troy ounce for contracts to be settled in December 2025, indicating that gold traders expect the price of gold to rise over the next five years. Gold futures are contracts that effectively lock in a price for an amount of gold to be purchased at a time in the future, which can then be traded on markets. Futures markets therefore provide an indicator of how investors think a commodities market will develop in the future.

The price of gold per troy ounce increased considerably between 1990 and 2025, despite some fluctuations. A troy ounce is the international common unit of weight used for precious metals and is approximately **** grams. At the end of 2024, a troy ounce of gold cost ******* U.S. dollars. As of * June 2025, it increased considerably to ******** U.S. dollars. Price of – additional information In 2000, the price of gold was at its lowest since 1990, with a troy ounce of gold costing ***** U.S. dollars in that year. Since then, gold prices have been rising and after the economic crisis of 2008, the price of gold rose at higher rates than ever before as the market began to see gold as an increasingly good investment. History has shown, gold is seen as a good investment in times of uncertainty because it can or is thought to function as a good store of value against a declining currency as well as providing protection against inflation. However, unlike other commodities, once gold is mined it does not get used up like other commodities (for example, such as gasoline). So while gold may be a good investment at times, the supply demand argument does not apply to gold. Nonetheless, the demand for gold has been mostly consistent.

View monthly updates and historical trends for All Commodities Excluding Gold Price Index. Source: International Monetary Fund. Track economic data with Y…

In 2025, the price of platinum is forecast to hover around ***** U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to ***** U.S. dollars. Precious metals Precious metals are counted among the most valuable commodities worldwide. The most well known such metals are gold, silver and the platinum group metals. A precious metal can be used as an industrial commodity or as an investment. The major areas of application include the following sectors: technology, car-making, industrial manufacturing and jewelry making. Furthermore, gold and silver are used as coinage metals, and gold reserves are held by the central banks of many countries worldwide in order to store value or for use as a redemption medium. The idea behind this procedure is that gold reserves will help secure and stabilize the countries’ respective currencies. At ***** tons, the United States is the country with the most extensive stock of gold. It is kept in an underground vault at the New York Federal Reserve Bank. Russia, the United States, Canada, South Africa and China are the main producers of precious metals. Silver is the most abundant of the metals, followed by gold and palladium. Barrick Gold is the world’s largest gold mining company. The Toronto-based firm produced some **** million ounces of gold in 2020. The leading silver producers include Mexico-based Fresnillo, Poland’s KGHM Polska Miedž and the mining giant Glencore. Anglo Platinum and Impala are the key mining companies to produce platinum group metals. In 2023, Silver prices are expected to settle at around **** U.S. dollars per troy ounce. It is expected to remain the precious metal with the lowest value per ounce. The price of gold is forecast to drop to around ***** U.S. dollars per ounce, making it the most expensive precious metal in 2023.

This data release contains the U.S. salient statistics and world production data extracted from the GOLD data sheet of the USGS Mineral Commodity Summaries 2024.

This comprehensive dataset contains 10 years of historical gold futures prices (2016-2026) sourced from Yahoo Finance, along with advanced machine learning predictions extending through December 2026. Perfect for financial analysis, time series forecasting, and machine learning enthusiasts.

Keywords: gold price prediction, time series forecasting, XGBoost, financial analysis, commodity trading, investment analysis, machine learning finance, gold futures, technical analysis, price forecasting

Historical Data Columns:** - Date (index) - Open, High, Low, Close prices (USD) - Volume - Adjusted Close Machine Learning Projects - Time series forecasting - Regression modeling - Feature engineering practice - Model comparison studies

✅ Financial Analysis - Investment strategy backtesting - Risk assessment - Trend analysis - Portfolio optimization

✅ Educational Purposes - Learning technical analysis - Understanding commodity markets - Practicing data visualization - Exploring EDA techniques

Model Performance

🤖 XGBoost Regression Model: - R² Score: 0.99+ (99%+ variance explained) - MAPE: <1% (prediction error) - RMSE: ~$15-20 (typical error range) - Training Set: 2,000+ samples - Test Set: 500+ samples

Data Source & Citation

Primary Source: Yahoo Finance (yfinance Python API) Ticker Symbol: GC=F (Gold Futures - COMEX) API: https://pypi.org/project/yfinance/ License: Educational and research purposes

This data release contains the U.S. salient statistics and world production data extracted from the GOLD data sheet of the USGS Mineral Commodity Summaries 2025.

This dataset can be used to predict the stock market. The data is extracted from MT5 terminal integrated in python.

The datasets include the minute by minute fluctuations of Gold and Silver prices over from 1st of January 2023 to 17th April 2025. The data can be used to train models for seasonality or a minute-by-minute approach.

The data has 7 columns:

• Time: The minute in which the event or movement occurred (Can be converted to Datetype with pd.to_datatime)
• Open Price
• High Price
• Low Price
• Close Price (The Feature to Predict if desired)
• Tick Volume: The Volume at the in which the event or movement occurred
• EMA: Exponential Moving Average (Technical Estimator for Risk management in the predictions and overall better performance)
• OBV: On-Balance Volume (Technical Estimator for Risk management in the predictions and overall better performance)

Two datasets are used;

Achilles Data Gold-Silver: with 1,416,340 rows to predict Gold, Silver and other Metals. Achilles Data Gold: with 708,264 rows to predict Gold, Silver and other Metals.

You may find the paper of our implementation here: https://doi.org/10.48550/arXiv.2410.21291

Germany Commodity Price: Precious Metals: Gold data was reported at 4,474.096 USD/Troy oz in 24 Mar 2026. This records an increase from the previous number of 4,407.857 USD/Troy oz for 23 Mar 2026. Germany Commodity Price: Precious Metals: Gold data is updated daily, averaging 1,506.784 USD/Troy oz from Jan 2013 (Median) to 24 Mar 2026, with 3353 observations. The data reached an all-time high of 5,393.867 USD/Troy oz in 29 Jan 2026 and a record low of 1,050.717 USD/Troy oz in 17 Dec 2015. Germany Commodity Price: Precious Metals: Gold data remains active status in CEIC and is reported by Deutsche Börse Group. The data is categorized under Global Database’s Germany – Table DE.P: Commodity Prices. [COVID-19-IMPACT]

Context

This is a news dataset for the commodity market where we have manually annotated 10,000+ news headlines across multiple dimensions into various classes. The dataset has been sampled from a period of 20+ years (2000-2021).

Content

The dataset has been collected from various news sources and annotated by three human annotators who were subject experts. Each news headline was evaluated on various dimensions, for instance - if a headline is a price related news then what is the direction of price movements it is talking about; whether the news headline is talking about the past or future; whether the news item is talking about asset comparison; etc.

Acknowledgements

Sinha, Ankur, and Tanmay Khandait. "Impact of News on the Commodity Market: Dataset and Results." In Future of Information and Communication Conference, pp. 589-601. Springer, Cham, 2021.

https://arxiv.org/abs/2009.04202 Sinha, Ankur, and Tanmay Khandait. "Impact of News on the Commodity Market: Dataset and Results." arXiv preprint arXiv:2009.04202 (2020)

We would like to acknowledge the financial support provided by the India Gold Policy Centre (IGPC).

Inspiration

Commodity prices are known to be quite volatile. Machine learning models that understand the commodity news well, will be able to provide an additional input to the short-term and long-term price forecasting models. The dataset will also be useful in creating news-based indicators for commodities.

Apart from researchers and practitioners working in the area of news analytics for commodities, the dataset will also be useful for researchers looking to evaluate their models on classification problems in the context of text-analytics. Some of the classes in the dataset are highly imbalanced and may pose challenges to the machine learning algorithms.

This data release contains the U.S. salient statistics and world production data extracted from the GOLD data sheet of the USGS Mineral Commodity Summaries 2022.

Japan Commodity Futures: Value: Average: Gold data was reported at 151.619 JPY bn in Oct 2018. This records an increase from the previous number of 134.579 JPY bn for Sep 2018. Japan Commodity Futures: Value: Average: Gold data is updated monthly, averaging 154.973 JPY bn from May 2004 (Median) to Oct 2018, with 174 observations. The data reached an all-time high of 411.077 JPY bn in Sep 2011 and a record low of 61.931 JPY bn in Apr 2005. Japan Commodity Futures: Value: Average: Gold data remains active status in CEIC and is reported by The Tokyo Commodity Exchange. The data is categorized under Global Database’s Japan – Table JP.Z017: Commodity Futures.