Gold rose to 3,320.86 USD/t.oz on July 1, 2025, up 0.53% from the previous day. Over the past month, Gold's price has fallen 1.80%, but it is still 42.51% 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 July of 2025.

Gold prices in , May, 2025 For that commodity indicator, we provide data from January 1960 to May 2025. The average value during that period was 596.56 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 3309.49 USD per troy ounce in May 2025. | TheGlobalEconomy.com

Monthly gold prices in USD since 1833 (sourced from the World Gold Council). The data is derived from historical records compiled by Timothy Green and supplemented by data provided by the World Bank...

Ghana Commodity Price: Gold data was reported at 1,281.100 USD/Fine oz in Jun 2018. This records a decrease from the previous number of 1,303.000 USD/Fine oz for May 2018. Ghana Commodity Price: Gold data is updated monthly, averaging 1,182.900 USD/Fine oz from Dec 2003 (Median) to Jun 2018, with 175 observations. The data reached an all-time high of 1,770.130 USD/Fine oz in Aug 2011 and a record low of 384.730 USD/Fine oz in May 2004. Ghana Commodity Price: Gold data remains active status in CEIC and is reported by Bank of Ghana. The data is categorized under Global Database’s Ghana – Table GH.P001: Commodity Price.

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.

Germany Commodity Price: Precious Metals: Gold data was reported at 3,232.079 USD/Troy oz in 15 May 2025. This records an increase from the previous number of 3,180.971 USD/Troy oz for 14 May 2025. Germany Commodity Price: Precious Metals: Gold data is updated daily, averaging 1,419.728 USD/Troy oz from Jan 2013 (Median) to 15 May 2025, with 3135 observations. The data reached an all-time high of 3,422.638 USD/Troy oz in 06 May 2025 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]

Time series of major commodity prices and indices including iron, cooper, wheat, gold, oil. Data comes from the International Monetary Fund (IMF).All rights are reservedDataDataset contains Monthly prices for 53 commodities and 10 indexes, starting from 1980 to 2016, Last updated on march 17, 2016. The reference year for indexes are 2005 (meaning the value of indexes are 100 and all other values are relative to that year).LicenseThe IMF grants permission to visit its Sites and to download and copy information, documents, and materials from the Sites for personal, noncommercial usage only, without any right to resell or redistribute or to compile or create derivative works, subject to these Terms and Conditions of Usage and also subject to more specific restrictions that may apply to particular information within the Sites. Any rights not expressly granted herein are reserved.For more information please visit: Copyright and Usage.

In 2025, the price of platinum is forecast to hover around 1,150 U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to 1,700 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 8,100 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 five 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 23.5 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 1,663 U.S. dollars per ounce, making it the most expensive precious metal in 2023.

Interactive chart of historical data for real (inflation-adjusted) gold prices per ounce back to 1915. The series is deflated using the headline Consumer Price Index (CPI) with the most recent month as the base. The current month is updated on an hourly basis with today's latest value.

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.

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.

Graph and download economic data for Producer Price Index by Commodity: Miscellaneous Products: Jewelry, Gold and Platinum (WPU15940222) from Dec 2011 to May 2025 about platinum, jewelry, gold, miscellaneous, commodities, PPI, inflation, price index, indexes, price, and USA.

NCDEX: Spot Price: Gold Premium/Discount: Ahmedabad: Second Session data was reported at -12.000 USD/Troy oz in 15 May 2025. This records a decrease from the previous number of -11.750 USD/Troy oz for 14 May 2025. NCDEX: Spot Price: Gold Premium/Discount: Ahmedabad: Second Session data is updated daily, averaging -4.000 USD/Troy oz from Jan 2023 (Median) to 15 May 2025, with 578 observations. The data reached an all-time high of 28.000 USD/Troy oz in 23 Jul 2024 and a record low of -78.000 USD/Troy oz in 18 Jul 2024. NCDEX: Spot Price: Gold Premium/Discount: Ahmedabad: Second Session data remains active status in CEIC and is reported by National Commodity & Derivatives Exchange Limited. The data is categorized under India Premium Database’s Price – Table IN.PB001: Commodities Spot Price: National Commodity & Derivatives Exchange Limited.

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.

Gold: A Brighter Future Ahead?

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

Analysis of ‘Sentiment Analysis of Commodity News (Gold)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ankurzing/sentiment-analysis-in-commodity-market-gold on 14 February 2022.

--- Dataset description provided by original source is as follows ---

Context

This is a news dataset for the commodity market where we have manually annotated 11,412 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.

--- Original source retains full ownership of the source dataset ---

Explore the factors affecting gold prices, including inflation, interest rates, supply and demand dynamics, currency fluctuations, and geopolitical events, and learn how these elements influence gold's value in the global market.

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.

Machine Learning Models for Gold Price Prediction

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 chart tracks the price of gold in U.S. dollars over the last 10 years.

United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores was 444.72200 Index Jun 1985=100 in December of 2021, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores reached a record high of 515.90000 in August of 2020 and a record low of 78.40000 in April of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores - last updated from the United States Federal Reserve on July of 2025.

Predictions: S&P GSCI Gold index is expected to continue its upward trend in the near term, driven by safe-haven demand amid ongoing geopolitical uncertainties and concerns about global economic growth. The index may face some resistance at higher levels, but it is likely to break through and reach new highs. Risks: The main risks to the S&P GSCI Gold index's upward trend include a significant improvement in the global economic outlook, a sharp decline in geopolitical tensions, and a shift in investor sentiment towards riskier assets. A prolonged period of high inflation could also pose a risk to the index, as investors may seek alternative safe-haven assets such as bonds.