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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.
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.
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Gold rose to 3,335.24 USD/t.oz on July 4, 2025, up 0.27% from the previous day. Over the past month, Gold's price has fallen 0.52%, but it is still 39.50% 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.
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Graph and download economic data for Producer Price Index by Commodity: Metals and Metal Products: Gold Ores (WPU102105) from Jun 1985 to Dec 2021 about ore, gold, metals, commodities, PPI, inflation, price index, indexes, price, and USA.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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 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.
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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.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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Gold prices, recently at $3,057.31, may drop to $1,820 due to supply-demand dynamics, interest rates, and new mines, says Morningstar's David Sekera.
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As of 2023, the global market size for precious metals is valued at approximately $250 billion, and it is projected to reach around $370 billion by 2032, with a compound annual growth rate (CAGR) of 4.3%. This robust growth is driven by several factors, including increasing demand from emerging markets, heightened investment interests, and technological advancements in industrial applications. Precious metals, particularly gold and silver, have long been valued as safe-haven assets, but recent trends indicate a broader scope of applications, which is further fueling market expansion.
The growth of the precious metal market is significantly influenced by the geopolitical climate and economic uncertainties. In times of political instability or economic downturns, investors often turn to precious metals as a means of preserving wealth, which in turn spikes demand. For instance, during periods of inflation or currency devaluation, gold and silver are particularly sought after as they retain intrinsic value. Moreover, central banks around the world have been bolstering their gold reserves, a move that not only stabilizes their own currencies but also adds upward pressure on gold prices, thereby contributing to market growth.
Another notable driver of the precious metal market is the growing industrial demand, especially for metals like silver and platinum. Silver, with its excellent electrical conductivity, is widely used in electronics and solar panels. Meanwhile, platinum finds extensive applications in automotive catalytic converters. As industries adopt greener technologies and renewable energy solutions, the demand for these metals is expected to rise. Additionally, advancements in medical technology and the growing use of silver in antibacterial applications are further broadening the scope of industrial demand for precious metals.
The jewelry sector continues to be a substantial contributor to the precious metal market. Gold and silver jewelry remain highly valued across various cultures, symbolizing wealth and prestige. The rise in disposable income coupled with changing fashion trends in emerging economies is driving the demand for both traditional and contemporary jewelry design, thereby bolstering market growth. Moreover, the increasing influence of online platforms has made luxury jewelry more accessible to a broader audience, further enhancing market reach.
Silver Bullion plays a pivotal role in the investment landscape, offering a tangible asset that investors can physically hold. Unlike digital investments, silver bullion provides a sense of security and ownership that is often appealing during times of economic uncertainty. The demand for silver bullion is influenced by its affordability compared to gold, making it an attractive option for both new and seasoned investors. Additionally, silver bullion is not only a store of value but also a hedge against inflation, protecting purchasing power over time. As global markets fluctuate, the stability and reliability of silver bullion continue to draw interest from a diverse range of investors seeking to diversify their portfolios.
Regionally, Asia Pacific dominates the precious metal market, driven largely by high consumption in countries such as China and India. The cultural affinity towards gold in these regions, especially during festivals and weddings, underpins the demand. Europe and North America also represent significant markets, with a strong focus on investment and industrial applications. Meanwhile, emerging markets in Latin America and the Middle East & Africa are projected to exhibit a higher growth rate due to increasing industrialization and rising disposable incomes.
The precious metal market is segmented into various types, including gold, silver, platinum, palladium, and others. Gold remains the most prominent segment, accounting for a substantial portion of the market share. Its allure as a hedge against inflation and economic instability makes it a favored choice among investors. Furthermore, gold's intrinsic value and historical significance continue to make it a preferred asset for central banks and institutional investors. The jewelry sector also heavily relies on gold, with countries like India and China leading the demand, driven by cultural and traditional practices.
Silver follows gold in terms of market significance, primarily due to its dual role as both an industrial and inv
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Between January 1971 and May 2025, gold had average annual returns of **** percent, which was only slightly more than the return of commodities, with an annual average of around eight percent. The annual return of gold was over ** percent in 2024. What is the total global demand for gold? The global demand for gold remains robust owing to its historical importance, financial stability, and cultural appeal. During economic uncertainty, investors look for a safe haven, while emerging markets fuel jewelry demand. A distinct contrast transpired during COVID-19, when the global demand for gold experienced a sharp decline in 2020 owing to a reduction in consumer spending. However, the subsequent years saw an increase in demand for the precious metal. How much gold is produced worldwide? The production of gold depends mainly on geological formations, market demand, and the cost of production. These factors have a significant impact on the discovery, extraction, and economic viability of gold mining operations worldwide. In 2024, the worldwide production of gold was expected to reach *** million ounces, and it is anticipated that the rate of growth will increase as exploration technologies improve, gold prices rise, and mining practices improve.
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Core consumer prices in the United States increased 2.80 percent in May of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
In December 2022, the monthly retail price inflation of gold, silver, and jewelry in China ranged at 8.4 percent, compared to the same month of the previous year. The inflation rate for jewelry has gradually picked up since August 2021.
The publication of retail price inflation rates has been discontinued by the National Bureau of Statistics of China in the beginning of 2023.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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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.
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The Consumer Price Index in the United States increased 0.10 percent in May of 2025 over the previous month. This dataset provides - United States Inflation Rate MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Graph and download economic data for Producer Price Index by Industry: Gold Ore and Silver Ore Mining (PCU2122221222) from Dec 1984 to Aug 2018 about silver, ore, gold, mining, PPI, industry, inflation, price index, indexes, price, and USA.
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Gold prices have hit record highs above $3,000 per ounce, driven by increased demand for safe-haven assets. Central banks' buying sprees and inflation concerns underscore gold's appeal amid global economic shifts.
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Gold prices hit a record high above $3,050 per ounce due to economic forecasts and Federal Reserve policy decisions, making gold an attractive investment amid rising inflation and declining US dollar and Treasury yields.
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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.