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

Silver rose to 36.89 USD/t.oz on July 4, 2025, up 0.10% from the previous day. Over the past month, Silver's price has risen 3.44%, and is up 18.18% 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 July of 2025.

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.

Predicting Silver Prices with Machine Learning: Promising Approaches and Considerations

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

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.

China Warehouse Stock: Shanghai Future Exchange: Silver data was reported at 932.184 Ton in 13 May 2025. This records an increase from the previous number of 924.953 Ton for 12 May 2025. China Warehouse Stock: Shanghai Future Exchange: Silver data is updated daily, averaging 1,318.760 Ton from Jul 2012 (Median) to 13 May 2025, with 3124 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.

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 >>

Interactive chart of historical data for real (inflation-adjusted) silver 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.

First Majestic 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: 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

Fortuna Silver Mines stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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.

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.

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

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.

📈 Daily Historical Stock Price Data for Discovery Silver Corp. (2014–2025)

A clean, ready-to-use dataset containing daily stock prices for Discovery Silver Corp. from 2014-10-24 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: Discovery Silver Corp. Ticker Symbol: DSV.TO Date Range: 2014-10-24 to 2025-05-28 Frequency: Daily Total Records: 2658 rows (one per… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-discovery-silver-corp-20142025.

MAG Silver market cap as of June 23, 2025 is $1.61B. MAG Silver market cap history and chart from 2010 to 2025. Market capitalization (or market value) is the most commonly used method of measuring the size of a publicly traded company and is calculated by multiplying the current stock price by the number of shares outstanding.

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 eight percent. Conversely, rest of the top five companies saw their share price decline over this period.

This dataset is about stocks. It has 3 rows and is filtered where the company is Silver Spruce Resources. It features 8 columns including stock name, company, exchange, and exchange symbol.

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