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.

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.

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

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...

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

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.

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.

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

The Gold Prices dataset includes daily prices of Gold since April 1968.

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 ---

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

The daily spot price of gold (OTC market).........

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

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

This dataset was created by Simon Wildsmith

Contents

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.

How does stagflation affect gold prices?

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.

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

Interactive chart of historical daily platinum prices back to 1985. The price shown is in U.S. Dollars per troy ounce.

📈 Daily Historical Stock Price Data for Greatland Gold plc (2006–2025)

A clean, ready-to-use dataset containing daily stock prices for Greatland Gold plc from 2006-07-03 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: Greatland Gold plc Ticker Symbol: GGP.L Date Range: 2006-07-03 to 2025-05-28 Frequency: Daily Total Records: 4776 rows (one per trading day)… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-greatland-gold-plc-20062025.

Analysis of ‘Gold Historical Datasets’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nward7/gold-historical-datasets on 28 January 2022.

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

Content

This contains data files of gold historical data (USD).

Date : Date of observation Price: The official price of the given day, month, or year Open : Opening price on the given day, month, or year High : Highest price on the given day, month, or year Low : Lowest price on the given day, month, or year Volume : Volume of transactions on the given day, month, or year Change %: Percent change of the previous and current (day, month, or year) price.

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