Gold fell to 3,350.92 USD/t.oz on July 14, 2025, down 0.18% from the previous day. Over the past month, Gold's price has fallen 0.98%, but it is still 38.32% 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 , June, 2025 For that commodity indicator, we provide data from January 1960 to June 2025. The average value during that period was 600.07 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 3352.66 USD per troy ounce in June 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...

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 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.

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.

The average monthly prices for gold increased worldwide between January 2014 and May 2025, although with some fluctuations. In January 2014, the average monthly price for gold worldwide stood at ******** nominal U.S. dollars per troy ounce. Significant jumps in the gold prices were observed, especially in the periods of uncertainty, as the investors tend to see gold as a safe investment option. For instance, the Corona pandemic acted as a shock to the economy, resulting in substantial increases in gold prices in 2020. As of May 2025, gold valued at ******** U.S. dollars per ounce, the highest value reported during this period.

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.

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.

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.

Dataset

This dataset was created by Phuc Le

Contents

Analysis of ‘Daily Gold Price (2015-2021) Time Series’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nisargchodavadiya/daily-gold-price-20152021-time-series on 13 February 2022.

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

Content

Daily gold prices (2014-01-01 to 2021-12-29)

Acknowledgements

Raw Data Source: https://in.investing.com/commodities/gold-mini This data frame is preprocessed to time series analysis and forecasting

Inspiration

Forecast, Predict Prices, Time Series Forecasting

Note

Gold Prices in this dataset makes no guarantee or warranty on the accuracy or completeness of the data provided.

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

As of June 25, 2024, gold futures contracts to be settled in June 2030 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 June 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.

As of May 2025, the London (morning fixing) price of an ounce of gold cost an average of ******** U.S. dollars, a slight increase compared to the average monthly morning fixing price of ******** U.S. dollars per ounce in the previous month.

London fixing gold price In January 2020, the average price for an ounce of fine gold was ******** U.S. dollars. It increased to ******** U.S. dollars as of April 2022. Although the monthly price for fine gold fluctuates, the average annual price of fine gold is gradually increasing. In 2001, the price for one ounce of gold was *** U.S. dollars, and by 2012 the price had risen to some ***** U.S. dollars. By 2024, the annual average gold price was nearly ***** dollars per ounce. In that year, global gold demand reached ******* metric tons worldwide. Price determinants of fine gold Fine gold is considered to be almost pure gold, where the value of the metal depends on the percentage of fineness. Twenty-four-carat gold is considered fine gold (from 99.9 percent gold by mass and higher). The London Gold Fix acts as a benchmark for the price of gold. The price of gold is set by the members of the London Gold Market Fixing Ltd undertaken by Barclays and its other members. The price is determined twice per business day at 10:30 am and 3:00 pm based on the London bullion market to settle contracts within the bullion market. The price is based on the equilibrium point between supply and demand agreed upon by participating banks. Gold prices must remain flexible, and gold fixing provides an instantaneous price at specified times.

This dataset is designed for the commodity market, featuring over 10,000 manually annotated news headlines. It aims to provide deep insights into news sentiment and its implications for commodity prices. The headlines were collected from various news sources and evaluated by three subject experts over a period of more than 20 years, from 2000 to 2021. Each news item has been assessed across multiple dimensions, including implied price direction (up, down, or constant), whether the news discusses past or future events, and if it involves asset comparisons. This dataset is particularly valuable for developing machine learning models that can understand commodity news, which can then serve as an additional input for both short-term and long-term price forecasting models. It is also useful for creating news-based indicators for commodities. Researchers focused on text analytics and classification problems will find this dataset beneficial, although some classes are highly imbalanced, which may present challenges for machine learning algorithms.

Columns

The dataset includes the following columns:

• Dates: The date of the news headline.
• URL: The URL where the news headline was published.
• News: The actual news headline text.
• Price Direction Up: A binary indicator (1 for Yes, 0 for No) if the news headline suggests an increase in price.
• Price Direction Constant: A binary indicator (1 for Yes, 0 for No) if the news headline suggests a stable price (no change).
• Price Direction Down: A binary indicator (1 for Yes, 0 for No) if the news headline suggests a decrease in price.
• Asset Comparison: A binary indicator (1 for Yes, 0 for No) if the news headline compares different assets.
• Past Information: A binary indicator (1 for Yes, 0 for No) if the news headline refers to past events.
• Future Information: A binary indicator (1 for Yes, 0 for No) if the news headline refers to future events.
• Price Sentiment: The overall sentiment of the gold commodity price based on the headline, categorised as positive, negative, or other.

Distribution

The dataset contains over 10,000 unique news headlines and corresponding metadata. Data files are typically provided in CSV format. Key distribution statistics for some dimensions are as follows:

• Dates: 3,761 unique values.
• URL: 10,570 unique values.
• News: 10,570 unique values.
• Price Direction Up: 6,158 headlines do not imply up, 4,412 imply up.
• Price Direction Constant: 10,126 headlines do not imply constant, 444 imply constant.
• Price Direction Down: 6,658 headlines do not imply down, 3,912 imply down.
• Asset Comparison: 8,569 headlines do not compare assets, 2,001 compare assets.
• Past Information: 318 headlines do not discuss past information, 10,252 discuss past information.
• Future Information: 10,251 headlines do not discuss future information, 319 discuss future information.
• Price Sentiment: Approximately 42% positive, 36% negative, and 22% other sentiment.

Usage

This dataset is ideally suited for:

• Developing machine learning models that understand commodity news for price forecasting.
• Creating news-based indicators for commodity markets.
• Evaluating text classification models in the context of news analytics.
• Research into the impact of news on commodity market volatility.

Coverage

The dataset has a global regional coverage. It spans a significant time range of over 20 years, from 2000 to 2021, with headlines collected across this period. There are no specific demographic notes beyond the focus on gold commodity news.

License

CC-BY-NC

Who Can Use It

This dataset is primarily intended for:

• Researchers and practitioners specialising in news analytics for commodities, who can leverage it for building predictive models.
• Data scientists and machine learning engineers working on text classification and natural language processing tasks, especially those dealing with imbalanced datasets.
• Financial analysts and market strategists interested in incorporating news sentiment into their commodity market analysis.

Dataset Name Suggestions

• Gold News Sentiment Analysis Dataset
• Commodity Market News Classifier
• Financial News Headline Sentiment
• Gold Price Direction News Data
• Annotated Commodity News for ML

Attributes

Original Data Source: Sentiment Analysis of Commodity News (Gold)

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 reserved

Dataset contains Monthly ...

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.

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

Context

Gold, the yellow shiny metal, has been the fancy of mankind since ages. From making jewelry to being used as an investment, gold covers a huge spectrum of use cases. Gold, like other metals, is also traded on the commodities indexes across the world. For better understanding time series in a real-world scenario, we will work with gold prices collected historically and predict its future value.

Content

Metals such as gold have been traded for years across the world. Prices of gold are determined and used for trading the metal on commodity exchanges on a daily basis using a variety of factors. Using this daily price-level information only, our task is to predict future price of gold.

Data

For the purpose of implementing time series forecasting technique , i will utilize gold pricing from Quandl. Quandl is a platform for financial, economic, and alternative datasets. To access publicly shared datasets on Quandl, we can use the pandas-datareader library as well as quandl (library from Quandl itself). The following snippet shows a quick one-liner to get your hands on gold pricing information since 1970s.

import quandl gold_df = quandl.get("BUNDESBANK/BBK01_WT5511")

The time series is univariate with date and time feature

Starter Kernel(s)

-Start with Fundamentals: TSA & Box-Jenkins Methods

This notebook is an overview of TSA and traditional methods

Acknowledgements

For this dataset and tasks, i will depend upon Quandl. The premier source for financial, economic, and alternative datasets, serving investment professionals. Quandl’s platform is used by over 400,000 people, including analysts from the world’s top hedge funds, asset managers and investment banks.

Inspiration

• Forecast gold price

*If you find the data useful your upvote is an explicit feedback for future works, Have fun exploring data!*

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