Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% 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 December of 2025.

Between January 2018 and June 2024, the price of shares in the SPDR Gold Shares ETF (also known as the SPDR Gold Trust) increased, reaching over *** dollars per share. The SPDR Gold Shares ETF is one of the largest precious metal ETF by assets under management and one of the ten largest holders of gold in the world - meaning that each share is effectively ownership of a share of gold bullion. Shares are bought and sold on the New York Stock Exchange, while much of the ETF's gold is held in London.

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

This dataset contains daily historical data of major financial instruments and indexes from January 1, 2015, to August 15, 2025 . It includes the following columns:

SPX – S&P 500 Index daily closing prices.

GLD – SPDR Gold Shares ETF daily adjusted closing prices.

USO – United States Oil Fund ETF daily adjusted closing prices.

SLV – iShares Silver Trust ETF daily adjusted closing prices.

EUR/USD – Daily Euro to US Dollar exchange rate.

The data was collected from Yahoo Finance using the yfinance Python library. The dataset is intended for research, analysis, and educational purposes.

Index Time Series for SPDR® Gold Shares. The frequency of the observation is daily. Moving average series are also typically included. The Trust holds gold bars and from time to time, issues Baskets in exchange for deposits of gold and distributes gold in connection with redemptions of Baskets. The investment objective of the Trust is for the Shares to reflect the performance of the price of gold bullion, less the Trust"s expenses. The Sponsor believes that, for many investors, the Shares represent a cost-effective investment in gold.

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.

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 ******.

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

Dataset

This dataset was created by Yug Kaushik

Released under CC BY-NC-SA 4.0

Contents

This dataset contains the predicted prices of the asset SPDR Gold Shares Defichain over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Context

Gold is a highly liquid asset, which is no one’s liability, carries no credit risk, and is scarce, historically preserving its value over time. It also benefits from diverse sources of demand: as an investment, a reserve asset, jewellery, and a technology component. Since 1971, gold’s return has been similar to equities and outperformed bonds. In the last 20 years, gold outperformed most major asset classes and it’s global investment demand increased by an average of 15% per year. Through its dual nature as a consumer good and investment, gold has historically preserved its value. Unlike fiat currencies, gold can’t be printed, only mined — this explains in good part why it has consistently outperformed all major fiat currencies.

Content

1. Date: The date of the trading day.
2. Open: The opening price of the gold share on that day.
3. High: The highest price the gold share reached during the trading day.
4. Low: The lowest price the gold share reached during the trading day.
5. Close: The closing price of the gold share on that day.
6. WAP: Weighted Average Price, which is the average price at which all trades of the stock or asset were executed during the trading day.
   WAP = (Total Cost of Purchases / Total Quantity Purchased)
7. No. of Shares: The total number of shares traded on that day.
8. No. of Trades: The total number of trades executed on that day.
9. Total Turnover: The total value of all trades executed on that day.
10. Deliverable Quantity: The total number of shares that were actually delivered to buyers on that day.
11. % Deli. Qty to Traded Qty: The percentage of the total traded quantity of shares that were actually delivered to buyers on that day.
12. Spread H-L: The difference between the highest and lowest prices of the gold share on that day.
13. Spread C-O: The difference between the closing and opening prices of the gold share on that day.

Context

SPDR Gold Shares (GLD) This fund buys gold bullion. The only time it sells gold is to pay expenses and honor redemptions​. Because of the ownership of bullion, this fund is extremely sensitive to the price of gold and will follow gold price trends closely.

One upside to owning gold bars is that no one can loan or borrow them. Another upside is that each share of this fund represents more gold than shares in other funds that do not buy physical gold. However, the downside is taxes. The Internal Revenue Service (IRS) considers gold a collectible, and taxes on long-term gains are high. (For more, see: The Most Affordable Way to Buy Gold: Physical Gold or ETFs?)

Content

Fund overview: CategoryCommodities Precious Metals Fund familySPDR State Street Global Advisors

Acknowledgements

Yahoo Finance

Inspiration

Dataset will be helpful for people who are looking to start playing the Time Series Analysis. What always got my attention was, when Dollar goes down DowJones and Nasdaq goes up and vice-versa. Can this dataset be used for creating a Causal Model?

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

Gold Road Resources 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: A Beacon for 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

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 Uncertain Future

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

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

This dataset represents typical financial time series data related to stock prices. Each column represents a specific type of information:

Date: The date on which the stock prices are recorded.

Open: The price of the stock at the beginning of the trading day (when the market opens).

High: The highest price of the stock during the trading day.

Low: The lowest price of the stock during the trading day.

Close: The price of the stock at the end of the trading day (when the market closes).

Adj Close (Adjusted Close): The closing price of the stock adjusted for dividends, stock splits, and other corporate actions. This provides a more accurate measure of the stock's performance for investors.

Volume: The number of shares traded on that particular day. In your data, some days have a volume value of '0', which might indicate a lack of data or no trading activity on that day.

Gold prices are essential for economic analysis and investment decisions. Gold is often seen as a safe-haven asset, especially during periods of market uncertainty. This data is used for technical analysis, trend analysis, and market forecasting.

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. 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.

Explore the potential of investing in the gold stock market for portfolio diversification, inflation hedging, and growth opportunities. Understand the risks and benefits of large-cap miners vs. junior exploration firms, and learn how to navigate geopolitical and regulatory factors, gold price fluctuations, and investment strategies like gold ETFs.