Gold fell to 4,023.41 USD/t.oz on October 27, 2025, down 2.15% from the previous day. Over the past month, Gold's price has risen 4.96%, and is up 46.60% 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 October of 2025.

Explore the dynamics of the gold market, including the factors affecting its price fluctuations and various investment options like ETFs and physical gold. Learn how geopolitical events and economic indicators influence gold as a safe-haven asset.

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

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.

View market daily updates and historical trends for Gold Price in US Dollars (DISCONTINUED). from United States. Source: Gold Council. Track economic data…

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

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.

Philadelphia Gold and Silver Index: The Future of Precious Metals?

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 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.

Gold Price Outlook: S&P GSCI Gold index Faces Volatility Amidst Economic Uncertainties

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

gold price dataset for a stock market analysis. Reference from Quandl https://www.quandl.com/

The size of the Gold Market was valued at USD 3.2 Trillion in 2023 and is projected to reach USD 4.5 Trillion by 2032, with an expected CAGR of 7.38% during the forecast period. It is one of the crucial financial assets with a liquid market, intrinsic value, and diversified uses in jewelry, electronics, and for investment purposes. Gold includes both the physical bullion and ETF markets. Mining and refining technological innovations enhance efficiency and sustainability.Gold provides economic stability and security of investments since it is durable, widely accepted, and one that diversifies portfolios. Hence, gold holds a very significant place both in consumer markets and financial systems through its support for industries ranging from luxury goods to technology. Recent developments include: March 2023: Pan American Silver Corporation acquired all the issued and outstanding common shares of Yamana Gold Inc., as part of the arrangement, which includes its mines and increased the geographical operations of the company in Latin America., February 2023: Barrick Gold, the world's second-biggest gold producer, announced a 10% increase in attributable proved and probable gold mineral reserves to 76 million ounces net of depletion in 2022 while maintaining current reserves.. Key drivers for this market are: Demand for Gold in the form of Jewelry and Long-term Savings, Increasing Consumption in High-End Electronics Applications; Other Drivers. Potential restraints include: Declining Ore Grades and Other Technical Challenges, Other Restraints. Notable trends are: Jewelry Segment to Dominate the Demand.

View market daily updates and historical trends for Gold Price in Euro (DISCONTINUED). Source: Gold Council. Track economic data with YCharts analytics.

Gold Bullion Market Outlook

According to our latest research, the global gold bullion market size reached USD 248.5 billion in 2024, and it is expected to grow at a CAGR of 4.7% during the forecast period, reaching approximately USD 373.4 billion by 2033. This healthy growth trajectory is primarily attributed to the increasing demand for safe-haven assets amid global economic uncertainties, rising geopolitical tensions, and a persistent appetite for portfolio diversification among both institutional and individual investors. The gold bullion market continues to benefit from its reputation as a reliable store of value, particularly during periods of inflation and currency depreciation, as per our comprehensive market analysis for 2025.

One of the most significant growth factors for the gold bullion market is the heightened volatility and uncertainty in global financial markets. Investors, both retail and institutional, are increasingly turning towards gold bullion as a hedge against inflation, currency fluctuations, and geopolitical risks. The persistent low-interest-rate environment, coupled with concerns over sovereign debt and fiscal imbalances in major economies, has further fueled the demand for physical gold. Central banks, especially in emerging markets, have been augmenting their gold reserves to diversify away from the US dollar and other fiat currencies, providing a strong and sustained impetus to the gold bullion market.

Another key driver propelling the gold bullion market is the growing accessibility and innovation in distribution channels. The proliferation of online platforms and digital gold investment products has democratized access to gold bullion, enabling a broader base of individual investors to participate in the market. This trend is further amplified by the introduction of fractional gold ownership, secure storage solutions, and transparent pricing mechanisms, which have collectively enhanced investor confidence and convenience. Additionally, the rise of gold-backed exchange-traded funds (ETFs) and other financial instruments has expanded the avenues for gold investment, reinforcing the market’s growth momentum.

Sustainability and ethical sourcing concerns are also shaping the gold bullion market landscape. Increasing awareness about responsible mining practices and the environmental and social impact of gold extraction has led to the emergence of certified, conflict-free bullion products. Regulatory initiatives and industry-led standards, such as the London Bullion Market Association (LBMA) Responsible Gold Guidance, are driving transparency and traceability across the supply chain. These developments are not only addressing investor concerns but also attracting a new segment of environmentally and socially conscious buyers, further supporting market expansion.

From a regional perspective, the Asia Pacific region remains the dominant force in the gold bullion market, driven by robust demand in countries like China and India, where gold holds deep cultural and economic significance. North America and Europe also represent substantial market shares, supported by strong institutional investment and central bank activity. Meanwhile, the Middle East & Africa and Latin America are emerging as important markets, buoyed by rising wealth levels, favorable regulatory environments, and increasing financial inclusion. The regional diversity in demand drivers underscores the global appeal and resilience of the gold bullion market.

Product Type Analysis

The gold bullion market is segmented by product type into bars, coins, rounds, and others, each catering to distinct investor preferences and use cases. Gold bars, often regarded as the standard investment vehicle for institutional buyers and high-net-worth individuals, account for the largest share of the market. Their appeal lies in their high purity, lower premiums over spot prices, and ease of storage and transport, making them the preferred choice for those seeking to make substantial investments in physical

The average gold price increased by 1.7% to $1800 per troy ounce in 2021. This year, it was forecast to ease, but rising political uncertainty may reverse the forecast.

Gold prices have fallen sharply as global stock markets rally and the US-China trade war shows signs of easing, reducing the demand for gold as a safe haven.

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.

Philadelphia Gold and Silver Index: A Beacon of Precious Metal Value?

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.

IAU:TSX i-80 Gold Corp.

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

As of April 2024, WisdomTree Core Physical Gold was the leading gold back exchange-traded commodity (ETC) listed on the London stock exchange, providing a return of 13 percent on euro investments annually. Invesco Physical Gold A followed closely in second place, providing a return of 12.86 percent on investments made in euros. What is an exchange-traded commodity? An exchange-traded commodity (ETC) is a commodity such as silver, wheat, oats, and gold traded on the stock exchange. Unlike exchange-traded funds (ETFs) which allows investment in a basket of securities, ETCs allow investment in a single commodity. Gold-backed ETCs aim to track the spot price of gold. This results in the price of the ETC moving up and down in correlation with the underlying gold price. The annual return rate The return on investment (ROI) is a way to measure the performance of an investment. The ROI is calculated by dividing the amount gained or lost from an investment by the original invested amount. This number is then represented as a percentage. Different gains and losses can be generated on foreign investments due to changes in the value of the security in foreign markets. If the local home currency of an investor is rising in value, this leads to lower returns on foreign investments. Similarly, a decreasing home currency will increase the returns on foreign investments. The difference in currency performance, inflation levels in the home market or abroad, and interest rates are all factors that can lead to differing ROI rates.

View market daily updates and historical trends for Gold Price in Japanese Yen (DISCONTINUED). Source: Gold Council. Track economic data with YCharts anal…

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.