Uranium fell to 76.90 USD/Lbs on October 20, 2025, down 1.41% from the previous day. Over the past month, Uranium's price has fallen 1.28%, and is down 6.90% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Uranium - values, historical data, forecasts and news - updated on October of 2025.

Graph and download economic data for Global price of Uranium (PURANUSDM) from Jan 1990 to Jun 2025 about uranium, World, and price.

View monthly updates and historical trends for Uranium Spot Price. Source: International Monetary Fund. Track economic data with YCharts analytics.

The average annual price for one pound of uranium was ******U.S. dollars in 2024. This is the highest annual average since 2007, and comes in the wake of greater fuel demand as the global economy began recovering from the coronavirus pandemic as well as the energy crisis.

Index Time Series for Global X Uranium Index ETF. The frequency of the observation is daily. Moving average series are also typically included. NA

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.

Uranium Energy Corp. (UEC) Outlook Positive Amidst Energy Transition

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

Index Time Series for Global X Uranium UCITS ETF USD Acc CHF. The frequency of the observation is daily. Moving average series are also typically included. NA

Nuclear Energy Index fell to 52.69 USD on October 20, 2025, down 1.88% from the previous day. Over the past month, Nuclear Energy Index's price has risen 3.93%, and is up 57.80% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Nuclear Energy Index.

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.

(AURA) Aura Energy: Uranium Powerhouse or Fading Hope?

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

Index Time Series for Global X Uranium UCITS ETF. The frequency of the observation is daily. Moving average series are also typically included.

Index Time Series for Sprott Uranium Miners UCITS ETF USD Accumulating GBP. The frequency of the observation is daily. Moving average series are also typically included. NA

Index Time Series for Sprott Junior Uranium Miners ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund will, under normal circumstances, invest at least 80% of its total assets in securities of the index. The index is designed to track the performance of companies that derive at least 50% of their revenue and/or assets from (i) mining, exploration, development, and production of uranium; (ii) earning uranium royalties; and/or (iii) supplying uranium. The index generally consists of from 30 to 40 constituents. The fund is non-diversified.