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.

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.

United States Index: Philadelphia Stock Exchange: Gold and Silver data was reported at 64.460 Jan1979=100 in Nov 2018. This records an increase from the previous number of 64.280 Jan1979=100 for Oct 2018. United States Index: Philadelphia Stock Exchange: Gold and Silver data is updated monthly, averaging 94.040 Jan1979=100 from Jan 1980 (Median) to Nov 2018, with 467 observations. The data reached an all-time high of 226.580 Jan1979=100 in Dec 2010 and a record low of 43.870 Jan1979=100 in Oct 2000. United States Index: Philadelphia Stock Exchange: Gold and Silver data remains active status in CEIC and is reported by Philadelphia Stock Exchange. The data is categorized under Global Database’s United States – Table US.Z014: Philadelphia Stock Exchange: Indexes.

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

The latest closing stock price for Barrick Gold as of May 23, 2025 is 19.07. An investor who bought $1,000 worth of Barrick Gold stock at the IPO in 1985 would have $45,592 today, roughly 46 times their original investment - a 10.08% compound annual growth rate over 40 years. The all-time high Barrick Gold stock closing price was 43.23 on April 21, 2011. The Barrick Gold 52-week high stock price is 21.35, which is 12% above the current share price. The Barrick Gold 52-week low stock price is 15.11, which is 20.8% below the current share price. The average Barrick Gold stock price for the last 52 weeks is 18.24. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

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

Graph and download economic data for CBOE Gold ETF Volatility Index from 2008-06-03 to 2025-07-11 about ETF, VIX, gold, volatility, stock market, and USA.

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.

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.

Among the five largest gold mining companies, Goldfields — headquartered in Johannesburg, South Africa-saw the largest growth in its share price recently. As of June 2025, the company had reached ****** index points. While all the top five mining companies experienced significant increase in their share prices over this period despite some fluctuations, Barrick Mining Corporation had the least increase when compared to others, with an index point of ******.

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

As of 31 May 2025, MSCI U.S. had an average **-year return rate of ***** percent, whereas gold had a return rate of ***** percent. Gold mining overview In light of recent technological advancements shaping the gold mining market, global gold production has been rather stable in the last few years, hovering around ***** metric tons since 2020. Among nations, Australia holds the highest gold production, surpassing countries with the highest mine gold reserves. Gold as a financial security Known for its ability to provide diversification to investment portfolios, gold has exhibited a positive trend in its Gold’s return rate was particularly high in the early 2000s, and, despite experiencing a decline during the pandemic, it demonstrated a remarkable recovery since. Furthermore, gold serves as a valuable asset for a nation's economic stability, with the United States holding the highest amount of

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.

S&P GSCI Gold Index: The Ultimate Gold Standard?

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

Content

Ticker Description 0 GC=F Gold 1 SI=F Silver 2 CL=F Crude Oil 3 ^GSPC S&P500 4 PL=F Platinum 5 HG=F Copper 6 DX=F Dollar Index 7 ^VIX Volatility Index 8 EEM MSCI EM ETF 9 EURUSD=X Euro USD 10 ^N100 Euronext100 11 ^IXIC Nasdaq 12 ^BSESN Bse sensex 13 ^NSEI Nifty 50 14 ^DJI Dow

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

South Africa ZA: Index: Share Price: Gold Mining data was reported at 75.879 2010=100 in 2016. This records an increase from the previous number of 42.218 2010=100 for 2015. South Africa ZA: Index: Share Price: Gold Mining data is updated yearly, averaging 84.730 2010=100 from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 305.237 2010=100 in 2006 and a record low of 8.226 2010=100 in 1961. South Africa ZA: Index: Share Price: Gold Mining data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s South Africa – Table ZA.IMF.IFS: Share Price Index: Annual.

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.

Is the S&P GSCI Gold Index a Reliable Guide to Gold's Performance?

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

South Africa Index: FTSE/JSE: Gold Mining data was reported at 1,059.759 02Jan2002=100 in Jun 2018. This records an increase from the previous number of 1,004.985 02Jan2002=100 for May 2018. South Africa Index: FTSE/JSE: Gold Mining data is updated monthly, averaging 2,217.340 02Jan2002=100 from Aug 2002 (Median) to Jun 2018, with 191 observations. The data reached an all-time high of 3,272.250 02Jan2002=100 in Jun 2006 and a record low of 796.932 02Jan2002=100 in Jul 2015. South Africa Index: FTSE/JSE: Gold Mining data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z001: Johannesburg Stock Exchange: Index.

This paper investigates whether gold and silver can be considered safe havens by examining their long-run linkages with 13 stock price indices. More specifically, the stochastic properties of the differential between gold/silver prices and 13 stock indices are analysed applying fractional integration/cointegration methods to daily data, first for a sample from January 2010 until December 2019, then for one from January 2020 until June 2022 which includes the Covid-19 pandemic. The results can be summarised as follows. In the case of the pre-Covid-19 sample ending in December 2019, mean reversion is found for the gold price differential only vis-à-vis a single stock index (SP500). whilst in seven other cases, although the estimated value of d is below 1, the value 1 is inside the confidence interval and thus the unit root null hypothesis cannot be rejected. In the remaining cases the estimated values of d are significantly higher than 1. As for the silver differential, the upper bound is 1 only in two cases, whilst in the others mean reversion does not occur. Thus, the evidence is mixed on whether these precious metals can be seen as safe havens, though it appears that this property characterises gold in a slightly higher number of cases. By contrast, when using the sample starting in January 2020, the evidence in favour of gold and silver as possible safe havens is pretty conclusive since mean reversion is only found in a single case, namely that of the gold differential vis-à-vis the New Zealand stock index.

Barrick Gold reported CAD50.66B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Barrick Gold | ABX - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.