Lithium fell to 72,450 CNY/T on September 12, 2025, down 0.55% from the previous day. Over the past month, Lithium's price has fallen 10.56%, and is down 0.07% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lithium - values, historical data, forecasts and news - updated on September 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.

Lithium Americas (LAC): Are batteries igniting growth?

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

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

Lithium Americas Corp.'s strong market position, expansion plans, and favorable industry tailwinds suggest continued growth. However, supply chain disruptions, commodity price fluctuations, and geopolitical risks pose uncertainties that could impact revenue and profitability.

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

In 2022, the average price of battery-grade lithium carbonate stood at ****** U.S. dollars per metric ton. This figure is by far the highest price for battery-grade lithium carbonate recorded in the period of consideration. For 2024, lithium carbonate price was estimated at ****** U.S. dollars per metric ton. Lithium is a highly reactive soft and silvery-white alkali metal. As the third element in the periodic table, it cannot be found in its pure form in nature. Lithium is the least dense of solid elements and the lightest out of all metals. Lithium and batteries One of lithium’s most well-known end uses is in lithium-ion batteries. Lithium-ion batteries are rechargeable and mostly used in portable electronics and electronic vehicles. In lithium-ion batteries, the lithium ions move from the negative electrode to positive electrode while in use, and the process is reversed while charging. These batteries are highly flammable but are also low-maintenance. They have a high energy density and a low self-discharge. Some drawbacks include the fact that they are expensive to manufacture, and that they require protection circuits to maintain the voltage safely. Lithium-ion batteries are also the single-largest end use of lithium, amounting to an ** percent share of global lithium consumption in 2024. Lithium demand forecasts Looking to the future, lithium demand is forecast to stand at *** million tons by 2025. This growth will be mainly driven by lithium-ion battery demand for electric vehicles. Demand is expected to remain the highest in China, which will consistently account for half of global lithium-ion battery 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.

Lithium Americas (LAC) - Riding the Electric Wave: A Forecast for Growth

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

Information about the largest lithium companies: Livent, Albemarle, Piedmont Lithium, Sociedad Química, FMC, Ganfeng Lithium (002460.SZ), Tianqi Lithium (002466.SZ).

Data is provided by day periods.

Columns: open price, high price, low price, close price, adj close and volume of stocks during the period.

Source: Yahoo finance

Lithium stocks rally on supply disruptions from China's Jianxiawo mine suspension, triggering major gains for producers like Sigma Lithium and Albemarle, though analysts warn the rally may be overextended.

Arcadium Lithium reported 389.6M in Stock for its fiscal quarter ending in September of 2024. Data for Arcadium Lithium | LTM - Stock including historical, tables and charts were last updated by Trading Economics this last September 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.

PLL Piedmont Lithium Inc. Common Stock

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

Arcadium Lithium reported 859.8M in Current Assets for its fiscal quarter ending in December of 2024. Data for Arcadium Lithium | LTM - Current Assets including historical, tables and charts were last updated by Trading Economics this last September 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.

S. Quimica Sees Lithium Demand Boosting (SQM) Stock's 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

Arcadium Lithium reported 3.78B in Market Capitalization this March of 2025, considering the latest stock price and the number of outstanding shares.Data for Arcadium Lithium | LTM - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last September 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.

EUR EUROPEAN LITHIUM LIMITED

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 global market size of Lithium Ion Battery Electrolyte Material is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Lithium Ion Battery Electrolyte Material Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Lithium Ion Battery Electrolyte Material industry. The key insights of the report:
1.The report provides key statistics on the market status of the Lithium Ion Battery Electrolyte Material manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Lithium Ion Battery Electrolyte Material industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Lithium Ion Battery Electrolyte Material Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Lithium Ion Battery Electrolyte Material as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Lithium Ion Battery Electrolyte Material market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
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* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
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We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

Arcadium Lithium reported 960.6M in Debt for its fiscal quarter ending in December of 2024. Data for Arcadium Lithium | LTM - Debt including historical, tables and charts were last updated by Trading Economics this last September in 2025.

Global lithium prices and stocks surged after CATL suspended operations at a key Chinese mine, raising fears of wider industry curbs and supply constraints.

The lithium carbonate market is experiencing robust growth, driven primarily by the burgeoning electric vehicle (EV) industry's insatiable demand for lithium-ion batteries. The market's Compound Annual Growth Rate (CAGR) of 23.22% from 2019 to 2024 indicates a significant upward trajectory. This rapid expansion is further fueled by increasing adoption of renewable energy storage solutions and the growing use of lithium carbonate in various applications beyond batteries, including pharmaceuticals, glass and ceramics, and aluminum production. While the market size for 2025 is not explicitly provided, projecting from the historical data and considering the CAGR, a reasonable estimate places the market value in the billions of dollars. The Asia-Pacific region, particularly China, holds a dominant market share, owing to its significant manufacturing capabilities and large EV market. However, North America and Europe are also experiencing strong growth, driven by government policies supporting EV adoption and renewable energy initiatives. The segmentation of the market by grade (technical, battery, industrial) and application highlights the diverse use cases and the potential for future expansion in specific niches. Challenges to the market include price volatility of lithium raw materials, geopolitical risks associated with lithium production and supply chains, and the environmental concerns surrounding lithium mining and processing. Overcoming these hurdles will be crucial for sustainable and consistent market growth in the coming years. The forecast period of 2025-2033 presents substantial opportunities for key players in the lithium carbonate market. Companies like Albemarle Corporation, SQM SA, and Ganfeng Lithium are well-positioned to capitalize on this growth, given their established production capacity and technological expertise. However, new entrants and technological advancements will continue to shape the competitive landscape. The increasing demand will necessitate investments in exploration, extraction, and processing infrastructure to meet the surging global needs. Furthermore, research and development into more sustainable and efficient lithium extraction and processing methods will be vital for addressing environmental concerns and ensuring long-term market viability. The continued growth in EV sales, coupled with advancements in battery technology, will likely sustain the strong growth of the lithium carbonate market throughout the forecast period, potentially exceeding the current projected CAGR based on continued innovation and investment. Recent developments include: January 2024: Allkem and Livent completed an all-stock merger to form Arcadium Lithium. This merger is a strategic move to incorporate the existing resources and expand the production and supplier scale. Arcadium focuses on highly complementary assets and a vertically integrated business model focused on enhancing operational flexibility and predictability while lowering costs., October 2023: General Motors Holdings LLC (GM) executed a second tranche subscription agreement to which GM will purchase Lithium Americas (NewCo) shares of USD 329.85 million. Through this agreement, GM has 100% exclusive rights to Thacker Pass Phase 1 production for ten years, which produces lithium chemicals, including lithium carbonate., May 2023: SQM SA and Ford Motor Company announced a long-term strategic agreement to supply high-quality battery-grade lithium carbonate, which is an essential component for the manufacturing of high-performance electric vehicle batteries.. Key drivers for this market are: Growing Demand From Lithium-ion Batteries, Increasing Investments in the Glass and Ceramics Industry. Potential restraints include: Growing Demand From Lithium-ion Batteries, Increasing Investments in the Glass and Ceramics Industry. Notable trends are: Li-Ion Battery Applications Expected to Drive Growth.

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.

Atlantic Lithium: Lithium Surge Ahead? (ALLI)

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