Silver rose to 37.68 USD/t.oz on August 12, 2025, up 0.16% from the previous day. Over the past month, Silver's price has fallen 1.15%, but it is still 35.37% higher than a year ago, 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 August of 2025.

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This statistic depicts the average annual prices for silver from 2014 through 2026*. In 2024, the average price for silver stood at 28.3 nominal U.S. dollars per troy ounce.

This statistic depicts the average monthly prices for silver worldwide from January 2014 through June 2025. In June 2025, the average monthly price for silver worldwide stood at ***** nominal U.S. dollars per troy ounce.

Silver prices in , July, 2025 For that commodity indicator, we provide data from January 1960 to July 2025. The average value during that period was 9.62 USD per troy ounce with a minimum of 0.91 USD per troy ounce in January 1960 and a maximum of 42.7 USD per troy ounce in April 2011. | TheGlobalEconomy.com

Dataset of historical annual silver prices from 1970 to 2022, including significant events and acts that impacted silver prices.

According to Cognitive Market Research, the global silver bullion market size is USD XX million in 2024 and will expand at a compound annual growth rate (CAGR) of 4.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 2.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD XX million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.0% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.4% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.7% from 2024 to 2031.
The US had the most significant global silver bullion market revenue share in 2024.

Market Dynamics of Silver Bullion Market

Key Drivers of Silver Bullion Market

Increasing Demand for Safe Haven Investments

The increasing wish for safe haven investments is driving the market for silver bullion to continue growing. Investors look for assets that deliver stability and wealth preservation throughout difficult economic, geopolitical, and market situations. Due to its inherent worth and historical importance as a wealth vault, silver is drawing more and more attention from investors trying to diversify their holdings and protect themselves from inflation and currency depreciation. The COVID-19 pandemic's aftereffects, trade disputes, and geopolitical tensions have all contributed to the current state of the global economy, which has raised investor anxieties and increased demand for silver bullion. Concerns about possible inflationary pressures are developing as governments execute large stimulus programs and central banks adopt loose monetary policies; this is pushing investors into physical assets like silver.

Increasing Industrial Applications Will Promote Market Expansion

The market for silver bullion is also expected to rise significantly due to the growing number of industrial uses. Due to its special qualities, which include its high conductivity, malleability, and resistance to corrosion, silver is used in a wide range of industries, including electronics, healthcare, automotive, and renewable energy. The industrial demand for silver is anticipated to grow in the upcoming years due to technological developments and advancements boosting demand in developing applications including solar panels, electric vehicles, and 5G technology. Silver's industrial demand is further bolstered by its antibacterial characteristics, which render it increasingly desirable in therapeutic applications. The market for silver bullion is expected to increase steadily as long as industries keep innovating and creating new goods that need silver. Investors who are eager to profit from the growing industrial need for this precious metal will be drawn to this market.

Restraint Factors Of Silver Bullion Market

Volatility in Precious Metal Prices will hinder market growth.

The price volatility of precious metals can have a substantial impact on the development of the silver bullion market. The price of silver can vary due to changes in currency values, geopolitical tensions, and global economic conditions. Investors get indeterminate as a result of these swings, which could make them unwilling to buy silver bullion. Investors who bought silver at higher prices may lose money as a result of abrupt price reductions, which could affect market liquidity and confidence. Businesses that use silver as a raw resource, such as manufacturers, face difficulties due to the unpredictable nature of silver pricing. Businesses may find it challenging to correctly manage expenses and plan production schedules in the face of shifting silver prices. Price variations can disrupt the supply chain, as suppliers and buyers are driving the changing market conditions.

Market participants may use hedging techniques or look for alternate investments to lessen the impact of price volatility, which could result in money being taken out of...

In 2024, the global silver market was finally on the rise to reach $65.1B for the first time since 2021, thus ending a two-year declining trend. Overall, consumption showed a relatively flat trend pattern. As a result, consumption reached the peak level of $65.6B. From 2022 to 2024, the growth of the global market failed to regain momentum.

Get the latest insights on price movement and trend analysis of Silver in different regions across the world (Asia, Europe, North America, Latin America, and the Middle East Africa).

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

The U.S. silver market rose remarkably to $7.5B in 2024, picking up by 6.4% against the previous year. Overall, consumption saw a relatively flat trend pattern. Over the period under review, the market hit record highs at $7.5B in 2012; afterwards, it flattened through to 2024.

In the first quarter (Q1) of 2025, the price per troy ounce of silver was approximately ** U.S. dollars worldwide. The price of silver rose from ***** to over ** U.S. dollars per troy ounce between Q1 and Q4 2024.

Silver prices have surged recently, driven by dynamics influencing gold. However, analysts remain cautious due to silver's intrinsic volatility and market uncertainties.

Explore the complex factors influencing silver prices, from economic conditions and market speculation to its dual role as a precious and industrial metal. Learn about supply dynamics, geopolitical influences, and the impact of mining on its value.

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

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.

Spot Price: Central Bank of Oman: Gold per Ounce: Buy data was reported at 1,229.680 OMR in 18 May 2025. This records an increase from the previous number of 1,208.530 OMR for 15 May 2025. Spot Price: Central Bank of Oman: Gold per Ounce: Buy data is updated daily, averaging 532.042 OMR from Dec 2007 (Median) to 18 May 2025, with 3830 observations. The data reached an all-time high of 1,337.450 OMR in 22 Apr 2025 and a record low of 0.105 OMR in 02 Jan 2022. Spot Price: Central Bank of Oman: Gold per Ounce: Buy data remains active status in CEIC and is reported by Central Bank of Oman. The data is categorized under World Trend Plus’s Commodity Market – Table OM.P001: Gold and Silver Spot Price. [COVID-19-IMPACT]

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

In 2024, the average nominal price of silver in India was ****** Indian rupees for one kilogram, which was an increase of over ****** rupees from the previous year, and the highest figure during the period of consideration.

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