Nickel rose to 15,218 USD/T on September 11, 2025, up 0.32% from the previous day. Over the past month, Nickel's price has fallen 0.92%, and is down 5.69% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Nickel - values, historical data, forecasts and news - updated on September of 2025.

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

The article provides an overview of the nickel stock market price, highlighting the factors that influence it, such as supply and demand dynamics, government policies, and global economic conditions. It also discusses the recent volatility in nickel prices due to the electric vehicle industry, the COVID-19 pandemic, and geopolitical events. Investors and traders interested in nickel stocks can use this information to make informed investment decisions.

The article explores the various factors that influence the nickel price in the stock market, including demand and supply dynamics, global economic conditions, and market speculation. It highlights the importance of nickel in various industries and how its price is closely tied to the growth and performance of these sectors. The article also discusses the impact of supply disruptions, changes in government policies, and demand from emerging economies on the nickel market. Additionally, it emphasizes the rol

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.

Nickel Index: The Future of the Metal?

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 price of nickel stock can be highly volatile and is influenced by various factors such as global demand, supply issues, economic stability, geopolitical events, and market speculation. This article explores how these factors impact the price of nickel stock and provides insights for investors in making informed investment decisions.

Norilsk Nickel 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.

Nickel Price Outlook: TR/CC CRB Nickel index Faces Volatility Amidst Shifting Supply Dynamics.

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

In May 2024, the price of one metric ton of nickel stood at some ********* U.S. dollars. In comparison, in December 2016, the price of nickel was just below ****** U.S. dollars per metric ton. Thus, the nickel price has increased considerably in recent years, though it continuously fluctuates. In the beginning of 2022, however, the price of nickel skyrocketed due to disruptions to supply chains and a wide scarcity of raw materials and metals. Overview of nickel Discovered in 1751, nickel is a base metal with a silvery-white lustrous appearance that has a slightly golden tinge. The metal is crucial for many global industries, especially, for example, for the production of stainless-steel. Nickel is highly corrosion-resistant and is used to plate other metals in order to protect them. Because of these useful traits, nickel is used in more than ******* products worldwide, spanning from architectural, industrial, military, transportation and aerospace, marine, currency, and consumer applications. Nickel price dynamics Though nickel is the fifth most abundant element found on Earth, as with any commodity, the price of nickel can vary widely depending on global market conditions. Following the collapse of the Soviet Union, exports of nickel increased dramatically, dropping the price of nickel in the mid-1990s to below production costs. Nickel production in the Western Hemisphere was reduced during that period. Prices then increased again, up to a high of ****** U.S. dollars per metric ton in May 2007. Since then, nickel prices have decreased, and have remained between a low of ***** U.S. dollars per metric ton and a high of ****** U.S. dollars per metric ton between 2016 and 2021. It is forecast that the price of nickel will amount to more than ****** U.S. dollars per metric ton in 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.

Nickel's Volatility May Impact TR/CC CRB Nickel index Forecast

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.

TR/CC CRB Nickel Index: A Reliable Gauge of Nickel Market Performance?

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

Investing in nickel mining stocks, ETFs, and futures contracts. Factors influencing nickel price, demand, and market dynamics. Research and industry knowledge essential for successful nickel investments.

Norilsk Nickel reported RUB4.8B in Stock for its fiscal semester ending in December of 2022. Data for Norilsk Nickel | GMKN - Stock including historical, tables and charts were last updated by Trading Economics this last September in 2025.

The Nickel Marketsize was valued at USD 36.27 USD Billion in 2023 and is projected to reach USD 51.38 USD Billion by 2032, exhibiting a CAGR of 5.1 % during the forecast period.Nickel is a transition metal, with atomic number of 28, bequeaths a variety of features and abilities as they are used in different fields. This is just a name that refers to its amazing, brilliant, silvery-white attribute that doesn't even depict its strength. This is why it is always used in stainless steel manufacturing. Thanks to its corrosion resistance nickel always helps all the alloys used in aerospace, construction, and healthcare, making them stable and durable and consequently long-living. The industrial consumption of nickel is absolutely not limited to the mentioned applications of this metal, as one of the decorative features for plating of jewellery pieces and coins, as it does demonstrate its beauty. While the advantage goes beyond the specialized purpose, nickel is one of the catalysts in industrial chemistry and its significant use in battery production is on the rise as the world seeks to adopt sustainable energy strategies. Despite the fact that the prices of the nickel commodity may go up or down, nickel's everlasting paramount role is kept high, and this enables forwarding of technology and human economy growth generally around the world. Hence, its history is a story made up of adaptable and dependable elements that can forever be associated with the persistence of the basis of an epoch-making institution for current civilizations. Key drivers for this market are: Rising Demand for Stainless Steel Fueled Ni Metal Consumption. Potential restraints include: Fluctuating Prices to Hamper Market Growth.

Norilsk Nickel reported RUB19.89B in Market Capitalization this September of 2025, considering the latest stock price and the number of outstanding shares.Data for Norilsk Nickel | GMKN - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last September in 2025.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Nickel prices skyrocketed on the expectations of a shortage on the global market provoked by the increase in demand that outpaces the supply growth. The rebound in the steel industry and rising electric vehicle manufacturing drive nickel consumption. Pandemic-related lockdowns in the first half of 2020 and the related uncertainty led to a decrease in the global nickel mine output by -4% y-o-y. Despite this, refined nickel production increased by +2% y-o-y, boosted by the recovering demand from mid-2020 and the use of secondary smelting. Indonesia, the largest nickel ore producer worldwide, banned exports of the ore and thus achieved a record output of refined nickel.

Nickel Mines reported $743.92M in Current Assets for its fiscal semester ending in December of 2024. Data for Nickel Mines | NIC - Current Assets including historical, tables and charts were last updated by Trading Economics this last September in 2025.

According to Cognitive Market Research, the global nickel market size is USD 35695.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 5.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 14278.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 10708.56 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 8209.90 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.0% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 1784.76 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.4% 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 713.90 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2024 to 2031.
The Electrical & Electronics End-Uses held the highest nickel market revenue share in 2024

Market Dynamics of Nickel Market

Key Drivers for Nickel Market

Increased Demand for Nickel Batteries to Increase the Demand Globally: One key driver in the nickel market is increased demand for nickel batteries. It is an essential component in the manufacture of lithium-ion batteries, which power electric vehicles. As the globe moves toward greener transportation and E.V. usage grows, so does the demand for nickel. Battery manufacture is projected to be a significant driver of nickel use in the coming years. Historically, the stainless steel sector was the major consumer of nickel. Nickel gives strength and corrosion resistance to steel, making it essential for a variety of applications. As global infrastructure development and industrial activity continue, demand for stainless steel, and thus nickel, remains high.

Boom in Electric Vehicles to Propel Market Growth: Another key driver in the nickel market is the increasing demand for electric vehicles. The worldwide electric vehicle (E.V.) boom is having a big impact on the nickel market, increasing both demand and prices. As the global demand for E.V.s grows, so does the demand for nickel to build these batteries. Major mining corporations such as BHP expect nickel demand to skyrocket in the coming decades, fuelled by the E.V. revolution. This boost in demand is putting strain on nickel supply, resulting in price increases. Nickel prices have already risen in recent years, and some predict that trend to continue as E.V. usage rises. Nickel has traditionally been used primarily in the stainless steel sector. However, the E.V. industry is expected to be the primary growth driver for nickel in the future.

Restraint Factor for the Nickel Market

Environmental and Health Issues to Limit the Sales: One key restraint in the nickel market is the challenge of Environmental and health issues. Nickel is an important metal in today's world. It is an important component of stainless steel, used in a variety of sectors, and used in lithium-ion batteries that power electric vehicles (E.V.s). The worldwide nickel market is expanding as demand for E.V.s rises. However, this expansion has a substantial drawback: environmental and health risks linked with nickel mining and processing. Nickel mining can pollute the air and water via dust, acid mine drainage, and inappropriate waste management. These pollutants can degrade ecosystems, taint drinking water, and impair respiratory health in adjacent communities. Nickel extraction and refining require a lot of energy, and it frequently uses fossil fuels, which contribute to greenhouse gas emissions.

Trends for the Nickel Market

Increasing Demand for Electric Vehicle (EV) Battery Production: The swift expansion of the electric vehicle sector is leading to a notable increase in the need for nickel, especially high-purity Class 1 nickel utilized in lithium-ion batteries. Automobile manufacturers are pursuing reliable sources of nickel to enhance battery energy density, prolong vehicle range, and lessen dependence on cobalt. This movement is transforming global nickel supply chains, prompting mining firms and battery producers to establish strategic alliances and invest in innovative extraction and refining technologies to sustai...

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.

Nickel Commodity Price Outlook: DJ Commodity Nickel Index Faces Volatility

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