Silver rose to 47.97 USD/t.oz on October 3, 2025, up 2.08% from the previous day. Over the past month, Silver's price has risen 17.95%, and is up 49.05% 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 October of 2025.

Explore the future price predictions of silver over the next five years, influenced by industrial demand, economic conditions, and geopolitical events. Learn how advances in technology, renewable energy trends, and global economic factors might drive silver prices, offering insights into potential market volatility and growth.

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).

Explore the complexities of silver price prediction, influenced by industrial demand, investment interest, geopolitical factors, and mining outputs. Understand how analysts use various tools to estimate future price movements amidst market uncertainties.

This dataset contains the predicted prices of Gram Silver for the upcoming years based on user-defined projections.

After two years of decline, the global silver market increased by 9.2% to $62.4B in 2024. In general, consumption, however, saw a relatively flat trend pattern. As a result, consumption reached the peak level of $65.1B. From 2022 to 2024, the growth of the global market remained at a somewhat lower figure.

In 2025, the price of platinum is forecast to hover around ***** U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to ***** U.S. dollars. Precious metals Precious metals are counted among the most valuable commodities worldwide. The most well known such metals are gold, silver and the platinum group metals. A precious metal can be used as an industrial commodity or as an investment. The major areas of application include the following sectors: technology, car-making, industrial manufacturing and jewelry making. Furthermore, gold and silver are used as coinage metals, and gold reserves are held by the central banks of many countries worldwide in order to store value or for use as a redemption medium. The idea behind this procedure is that gold reserves will help secure and stabilize the countries’ respective currencies. At ***** tons, the United States is the country with the most extensive stock of gold. It is kept in an underground vault at the New York Federal Reserve Bank. Russia, the United States, Canada, South Africa and China are the main producers of precious metals. Silver is the most abundant of the metals, followed by gold and palladium. Barrick Gold is the world’s largest gold mining company. The Toronto-based firm produced some **** million ounces of gold in 2020. The leading silver producers include Mexico-based Fresnillo, Poland’s KGHM Polska Miedž and the mining giant Glencore. Anglo Platinum and Impala are the key mining companies to produce platinum group metals. In 2023, Silver prices are expected to settle at around **** U.S. dollars per troy ounce. It is expected to remain the precious metal with the lowest value per ounce. The price of gold is forecast to drop to around ***** U.S. dollars per ounce, making it the most expensive precious metal in 2023.

This dataset contains the predicted prices of Silver for the upcoming years based on user-defined projections.

The U.S. silver market rose sharply to $7.5B in 2024, increasing by 6.2% against the previous year. Over the period under review, consumption showed a relatively flat trend pattern. Over the period under review, the market reached the peak level at $7.5B in 2012; afterwards, it flattened through to 2024.

This dataset contains the predicted prices of the asset Silver 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.

HSBC has revised its silver price projections upward, influenced by gold's surge and economic uncertainty, while noting potential shifts in industrial and investment demand.

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

HSBC predicts higher silver prices due to gold's rally, industrial demand, and potential Fed rate cuts. The bank forecasts $35.14/oz in 2025 with a persistent market deficit.

Explore the volatile price trends of silver, driven by industrial demand, investment interest, and macroeconomic factors. Discover how inflation, geopolitical tensions, and economic events influence silver prices, along with the impact of technological advancements and investment products.

This dataset contains the predicted prices of the asset Pure Silver 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.

Silver futures contracts to be settled in December 2028 were trading on U.S. markets at around ** U.S. dollars per troy ounce on June 20, 2023. This is above the price of ***** U.S. dollars per troy ounce for contracts to be settled in May 2024, indicating silver traders expect the price of silver to decrease over the next five years. Silver futures are contracts that effectively lock in a price for an amount of silver to be purchased at a time in the future, which can then be traded on markets. Futures markets therefore provide an indicator of how investors think a commodities market will develop in the future.

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

The MENA's silver market shrank to $3.1B in 2024, falling by -7.8% against the previous year. Overall, consumption, however, saw a relatively flat trend pattern. As a result, consumption attained the peak level of $3.5B. From 2022 to 2024, the growth of the market remained at a somewhat lower figure.

In 2024, the Nepalese silver market was finally on the rise to reach $64M for the first time since 2021, thus ending a two-year declining trend. In general, consumption enjoyed notable growth. Silver consumption peaked at $209M in 2015; however, from 2016 to 2024, consumption failed to regain momentum.

Silver Bullion Market Outlook 2032

The global silver bullion market size was USD XX Billion in 2023 and is projected to reach USD XX Billion by 2032, expanding at a CAGR of XX% during 2024–2032. The market growth is attributed to the rising consume preference of silver for investment purpose.



The silver bullion market is experiencing an increasing trend, driven by a variety of factors. As a tangible asset with intrinsic value, silver bullion offers a hedge against inflation and currency fluctuations, which is attracting more investors. The growing industrial demand for silver, particularly in the electronics and solar energy sectors, is also contributing to the rising interest in silver bullion.

The recent volatility in the global economy has led to a surge in the demand for safe-haven assets, presenting significant opportunities for the market. With these driving factors, the market is poised for further growth, offering a wealth of opportunities for investors and stakeholders alike.

Impact of Artificial Intelligence (AI) onSilver Bullion Market

Artificial Intelligence has a positive impact on the silver bullion market by enhancing predictive analysis and decision-making processes. Advanced AI algorithms analyze vast amounts of data, including historical silver prices, global economic indicators, and market trends, to generate accurate forecasts. These insights enable investors and market players to make informed decisions, thereby optimizing their investment strategies.



AI contributes to operational efficiency by automating routine tasks, reducing human error, and improving risk management. It also fosters transparency in the market by detecting and preventing fraudulent activities through pattern recognition and anomaly detection.

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