Gold fell to 3,372.61 USD/t.oz on July 24, 2025, down 0.45% from the previous day. Over the past month, Gold's price has risen 1.19%, and is up 42.68% 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 July of 2025.

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...

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

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.

Explore the dynamics of the spot market gold price, a critical real-time pricing mechanism influenced by global supply and demand. Understand how factors like geopolitical events, the U.S. dollar strength, and technological advancements impact gold's value. Learn about the role of the spread in gold trading and how online platforms have democratized access to gold market data.

Gold Fields stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Dataset historical price data for XAU/USD (gold vs USD) from 2004 to Feb 2025, captured across multiple timeframes including 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, daily, weekly, and monthly intervals. Dataset includes Open, High, Low, Close prices, and Volume data.

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 of historical annual gold prices from 1970 to 2024, including significant events and acts that impacted gold prices.

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

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

FINAL_USO Dataset

  Overview

The FINAL_USO dataset is a comprehensive collection of financial data, including stock prices, volumes, and other relevant metrics for various market indices and individual securities. This dataset is particularly suited for financial analysis, time series forecasting, and market trend analysis.

  Dataset Structure

The dataset is provided as a single CSV file named FINAL_USO.csv. It contains 1,718 entries and 80 columns, each… See the full description on the dataset page: https://huggingface.co/datasets/mltrev23/gold-price.

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.

Explore the fluctuating gold price per gram in the world market, influenced by key factors like interest rates, currency fluctuations, geopolitical events, inflation, and physical demand. Understand gold's role as a safe-haven asset and how its price dynamics offer insights during economic uncertainty.

In 2021, the global gold market decreased by -7.3% to $X for the first time since 2018, thus ending a two-year rising trend. The market value increased at an average annual rate of +3.1% from 2012 to 2021; however, the trend pattern indicated some noticeable fluctuations being recorded in certain years. Over the period under review, the global market reached the maximum level at $X in 2020, and then shrank in the following year.

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.

What happens to gold if CPI increases?

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

In 2024, one troy ounce of gold had an annual average price of ******** U.S. dollars. Gold pricing determinants Gold is a metal that is considered malleable, ductile, and is known for its bright lustrous yellow color. This transition metal is highly valued as a precious metal for its use in coins, jewelry, and in investments. Gold was also once used as a standard for monetary policies between different countries. The price of gold is determined by daily fixings where participants agree to buy or sell at a set price or to maintain the price through supply and demand control. For gold, companies like Barclays Capital, Scotia-Mocatta, Sociétè Générale, HSBC, and Deutsche Bank are members in gold fixing at the London Bullion Market Association.

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.

This document contains statistical data and analysis of global gold demand and prices from 2010 to 2024, presented by Dojipedia, a website focused on Forex investment information. The data is organized quarterly and includes various categories of gold demand such as jewelry fabrication, technology use, investment, and central bank purchases. It also provides the LBMA gold price in US dollars per ounce for each quarter.The document highlights significant events that influenced gold prices and demand during this period. These events include major economic crises, geopolitical tensions, and market shifts. For instance, it mentions the European debt crisis in 2010, the U.S. credit rating downgrade in 2011, the Federal Reserve's quantitative easing tapering signals in 2013, and the COVID-19 pandemic's impact starting in 2020.The data shows how gold demand and prices often increase during times of economic uncertainty or political instability, as investors view gold as a safe-haven asset. For example, gold prices reached record highs in 2024 amid global economic and geopolitical uncertainties.Dojipedia presents itself as a platform with five years of Forex market investment experience. The site offers free educational content on technical analysis methods such as Elliott Wave, ICT Trading, and Smart Money Concept. It also mentions plans to publish free books on technical analysis.The document includes a disclaimer stating that the information provided is for general purposes only and not financial advice. It warns about the high risks associated with investing in financial markets like CFDs, Forex, cryptocurrencies, and gold. The disclaimer emphasizes that leveraged products may not be suitable for all investors due to the high risk to capital.Overall, this document serves as a comprehensive resource for those interested in gold market trends and their relationship to global economic events over the past decade and a half.

Gold Bullion Market Outlook 2032

The global gold bullion market size was USD 50 Billion in 2023 and is likely to reach USD 133 Billion by 2032, expanding at a CAGR of 10.6% during 2024–2032. The market growth is attributed to the relative stability of gold investments.



Increasing economic uncertainties and geopolitical tensions are fueling the market. Investors are turning to gold as an asset, due to its inherent value and stability. The growing interest of central banks are leading them to expand their gold reserves. This allows them to diversify their holdings and reduce their dependence on the US dollar.

The growing popularity of gold-backed exchange-traded funds (ETFs) is propelling the market. These investments provide investors with exposure to the price movements of gold without the need to physically store the precious metal. The convenience and ease of investing in gold ETFs are attracting a new generation of investors, spurring the market.

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  According to a January 2024 report published by the World Gold Council, the total value of global gold ETFs rose by 6% to USD 2.4 Billion. This rise was due to a 15% hike in gold prices during 2023.

  
  

Impact of Artificial Intelligence (AI) in Gold Bullion Market

The use of artificial intelligence (AI) is likely to provide substantial propulsion to the gold bullion market. It is enhancing the efficiency and accuracy of gold trading with algorithms. These algorithms rapidly analyze vast amounts of data to make real-time trading decisions. This leads to increasingly profitable trades and reduces the risk of human error.


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