Silver fell to 57.28 USD/t.oz on December 2, 2025, down 1.22% from the previous day. Over the past month, Silver's price has risen 19.11%, and is up 84.81% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on December of 2025.

Explore how economic indicators, geopolitical stability, and industrial demand influence silver prices in the stock market and commodities trading. Learn about the impact of central banks' monetary policies and the role of silver in sectors like electronics and clean energy. Discover investment options like silver ETFs and mining stocks to diversify portfolios and manage market volatility.

MAG Silver 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

Stay informed with real-time charts of international precious metal prices. Monitor spot prices for Silver in USD, GBP, and EUR. Access live updates here >>

Of the five largest publicly owned produces of silver, Swiss multinational commodity trading and mining company Glencore saw an increase in its share price over recent years. Between January 2018 and March 2024, the share price of Glencore saw its share price increase by nearly ***** percent. Conversely, rest of the top five companies saw their share price decline over this period.

This dataset encapsulates a detailed examination of market dynamics over a five-year period, focusing on the fluctuation of prices and trading volumes across a diversified portfolio. It covers various sectors including energy commodities like natural gas and crude oil, metals such as copper, platinum, silver, and gold, cryptocurrencies including Bitcoin and Ethereum, and key stock indices and companies like the S&P 500, Nasdaq 100, Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta Platforms. This dataset serves as a valuable resource for analyzing trends and patterns in global markets.

Date: The date of the recorded data, formatted as DD-MM-YYYY. Natural_Gas_Price: Price of natural gas in USD per million British thermal units (MMBtu). Natural_Gas_Vol.: Trading volume of natural gas Crude_oil_Price: Price of crude oil in USD per barrel. Crude_oil_Vol.: Trading volume of crude oil Copper_Price: Price of copper in USD per pound. Copper_Vol.: Trading volume of copper Bitcoin_Price: Price of Bitcoin in USD. Bitcoin_Vol.: Trading volume of Bitcoin Platinum_Price: Price of platinum in USD per troy ounce. Platinum_Vol.: Trading volume of platinum Ethereum_Price: Price of Ethereum in USD. Ethereum_Vol.: Trading volume of Ethereum S&P_500_Price: Price index of the S&P 500. Nasdaq_100_Price: Price index of the Nasdaq 100. Nasdaq_100_Vol.: Trading volume for the Nasdaq 100 index Apple_Price: Stock price of Apple Inc. in USD. Apple_Vol.: Trading volume of Apple Inc. stock Tesla_Price: Stock price of Tesla Inc. in USD. Tesla_Vol.: Trading volume of Tesla Inc. stock Microsoft_Price: Stock price of Microsoft Corporation in USD. Microsoft_Vol.: Trading volume of Microsoft Corporation stock Silver_Price: Price of silver in USD per troy ounce. Silver_Vol.: Trading volume of silver Google_Price: Stock price of Alphabet Inc. (Google) in USD. Google_Vol.: Trading volume of Alphabet Inc. stock Nvidia_Price: Stock price of Nvidia Corporation in USD. Nvidia_Vol.: Trading volume of Nvidia Corporation stock Berkshire_Price: Stock price of Berkshire Hathaway Inc. in USD. Berkshire_Vol.: Trading volume of Berkshire Hathaway Inc. stock Netflix_Price: Stock price of Netflix Inc. in USD. Netflix_Vol.: Trading volume of Netflix Inc. stock Amazon_Price: Stock price of Amazon.com Inc. in USD. Amazon_Vol.: Trading volume of Amazon.com Inc. stock Meta_Price: Stock price of Meta Platforms, Inc. (formerly Facebook) in USD. Meta_Vol.: Trading volume of Meta Platforms, Inc. stock Gold_Price: Price of gold in USD per troy ounce. Gold_Vol.: Trading volume of gold

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The Silver Market Report is Segmented by Type (Fine Silver, Sterling Silver, Argentium Silver, Coin Silver, Other Types), Application (Physical Investment, Electrical and Electronics, Photographic Films, Brazing Alloys and Solders, Jewelry and Silverware, Pharmaceuticals and Biomedical, Other Applications), and Geography (Asia-Pacific, North America, Europe, South America, Middle-East and Africa).

Stock Price Time Series for Sprott Physical Silver. Sprott Physical Silver Trust is an exchange traded commodity launched and managed by Sprott Asset Management LP. The fund invests in the commodity markets. It primarily invests in physical silver bullion in London Good Delivery bar form. Sprott Physical Silver Trust was formed on June 30, 2010 and is domiciled in Canada.

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.

Silver's 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

This dataset can be used to predict the stock market. The data is extracted from MT5 terminal integrated in python.

The datasets include the minute by minute fluctuations of Gold and Silver prices over from 1st of January 2023 to 17th April 2025. The data can be used to train models for seasonality or a minute-by-minute approach.

The data has 7 columns:

• Time: The minute in which the event or movement occurred (Can be converted to Datetype with pd.to_datatime)
• Open Price
• High Price
• Low Price
• Close Price (The Feature to Predict if desired)
• Tick Volume: The Volume at the in which the event or movement occurred
• EMA: Exponential Moving Average (Technical Estimator for Risk management in the predictions and overall better performance)
• OBV: On-Balance Volume (Technical Estimator for Risk management in the predictions and overall better performance)

Two datasets are used;

Achilles Data Gold-Silver: with 1,416,340 rows to predict Gold, Silver and other Metals. Achilles Data Gold: with 708,264 rows to predict Gold, Silver and other Metals.

You may find the paper of our implementation here: https://doi.org/10.48550/arXiv.2410.21291

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.

Silver prices may remain elevated due to rising inflationary pressures and increased demand for safe-haven assets amid geopolitical uncertainties. However, potential risks include a stronger US dollar, reduced industrial activity due to economic slowdown, and volatility in equity markets.

The price of an ounce of silver increased sharply in 2021, rising around 17 percent from January 28 to February 1. The cause of this increase is attributed to retail investors mobilized via social media with the intention of causing losses to professional investors, similar to the rise in the stock price of video game retailer GameStop, and the stock price of cinema operator AMC several days beforehand. As of midnight July 18, 2023, the price of silver was trading at 24.9 U.S. dollars per troy ounce.

The size of the Silver Market was valued at USD 29.4 Billion in 2023 and is projected to reach USD 59.14 Billion by 2032, with an expected CAGR of 10.5% during the forecast period. Recent developments include: Silver market forecasts from 2021 and the upcoming years suggest that most key industrial players focus on exploring new technologies that can be merged with the silver market production. This greatly helps in the purchase of commodities. Several regulatory bodies are implemented for the detection and quality verification of the silver as well that disclose a proper commodity market. Not only consumers but also manufacturers and retailers help with the same. This now provides numerous opportunities for marketers due to the rising demand of the prominent key players of the market like Goldcorp, Gold Fields, and Barrick Gold.. Key drivers for this market are: Growing global population and rising disposable income. Increasing demand for silver in electronics and technology. Concerns about energy security and the need for renewable energy sources.. Potential restraints include: Price volatility and fluctuations in supply and demand. Competition from substitute materials, such as copper and aluminum. Stringent environmental regulations governing silver mining and processing activities.. Notable trends are: Development of new technologies for silver extraction and processing. Rising adoption of silver-based antimicrobial and antibacterial technologies. Growing interest in silver as a sustainable investment asset..

View monthly updates and historical trends for Silver Price. from United States. Source: World Bank. Track economic data with YCharts analytics.

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

China Warehouse Stock: Shanghai Future Exchange: Silver data was reported at 573.702 Ton in 01 Dec 2025. This records an increase from the previous number of 558.882 Ton for 28 Nov 2025. China Warehouse Stock: Shanghai Future Exchange: Silver data is updated daily, averaging 1,221.022 Ton from Jul 2012 (Median) to 01 Dec 2025, with 3261 observations. The data reached an all-time high of 3,091.112 Ton in 12 Jan 2021 and a record low of 0.000 Ton in 18 Jul 2012. China Warehouse Stock: Shanghai Future Exchange: Silver data remains active status in CEIC and is reported by Shanghai Futures Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Shanghai Futures Exchange: Commodity Futures: Stock.

Stock Price Time Series for Aya Gold & Silver Inc. Aya Gold & Silver Inc., together with its subsidiaries, engages in the exploration, evaluation, and development of precious metals projects in Morocco. The company primarily explores for gold and silver deposits. Its flagship project holds 100% interests in the Zgounder property located approximately 260 kms east of Agadir in the Proterozoic Siroua Massif of the Anti-Atlas Range, Morocco covering an area of approximately 350 square kilometers. The company was incorporated in 2007 and is based in Mount Royal, Canada.

Graph and download economic data for CBOE Silver ETF Volatility Index (DISCONTINUED) (VXSLVCLS) from 2011-03-16 to 2022-02-11 about silver, ETF, VIX, volatility, stock market, and USA.