Nuclear Energy Index rose to 37.79 USD on July 3, 2025, up 0.03% from the previous day. Over the past month, Nuclear Energy Index's price has risen 14.17%, and is up 27.20% 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.

NuScale Power (SMR): Redefining Nuclear Energy?

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

Prices for Nuclear Energy Index including live quotes, historical charts and news. Nuclear Energy Index was last updated by Trading Economics this July 3 of 2025.

NuScale Power Corp stock is predicted to have moderate volatility and medium-term growth potential. The company's strong position in the advanced nuclear reactor market and government support provide favorable conditions for its future performance. However, uncertainties surrounding the commercialization of its technology and regulatory approvals pose risks to investors considering the stock.

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.

BWX Technologies (BWXT) Nuclear Power Play: Will the Future Be Bright?

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.

Uranium Royalty Corp. (UROY): Will the King of Nuclear Energy Power its Way to Success?

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

Nano Nuclear Energy other share holders equity from 2024 to 2025. Other share holders equity can be defined as field containing the sum of all current assets that cannot be standardized into another field as well as those that are aggregated by the company because materially, they are too small to list separately.

If I were to boil the thesis down to a few bullets, I’d say: Uranium is an essential input for nuclear reactors with no substitute. Following the Fukushima disaster, there was a massive supply glut as reactors were taken offline due to safety concerns Now a supply crunch is looming, with a current market deficit of ~40m lbs Nuclear power plants usually contract uranium supplies several years out before their inventory gets run down. Due to the oversupply coming out of the previous cycle, however, they have been purchasing additional supply needs in the spot market instead of contracting years in advance. 13f filings indicate that the power plants’ coverage rates (contracted lbs of uranium supply / lbs of uranium required) are beginning to trend below 100%, indicating utilities have less locked-in supply than they need to keep running their reactors, at a time when market supply is tightening (note utilities typically look to maintain coverage ratios well above 100% to ensure no unforeseen shortfalls) Global demand for uranium is increasing, with ~56 new reactors under construction an a further 99 in planning currently. Nuclear power currently generates ~10% of the world’s electricity but with the closure of coal and fossil fuel power plants due to ESG considerations, nuclear energy is increasingly being seen as the only viable way to make up up the lost energy capacity. Putting all of this together, a fundamental supply/demand imbalance for an essential commodity with price insensitive buyers and ESG tailwinds makes the bull case extremely compelling. But a picture is worth a thousand words, so some historic charts probably best provide a sense of the future upside expected in the next cycle. Using the data of form 8k, at the peak of the previous uranium bull market in 2007 (when there was no supply deficit) the uranium spot price reached ~$136/lb after a run up from ~$15/share at the start of 2004 (~9x increase). Today the current price is ~$42/lb with the view that the price will reach new highs in this coming cycle: Many uranium investors, based on the majority of form 10q, focus on the miners rather than the commodity as being the way to play the new uranium bull market, as these are more levered to price increases in the underlying commodity. The share price for Canadian-based Cameco Corporation (CCO / CCJ, the second largest uranium producer in the world) increased from USD $3/share to $55/share ( ~18x bagger) during the previous bull market from ~2004 – 2007: While Cameco’s performance was impressive, it was not the biggest winner during the previous uranium bull market. Australian miner Paladin Energy ($PALAF) went from AUD $0.01 to AUD $10.70 (~1000x! ) between late 2003 and the market peak in Q1 2007, according to their stock price in Google Sheets: Similar multibagger returns for uranium stocks will be seen again if a new bull market in uranium materializes in the coming 2-3 years when utilities’ uranium supply falls to inoperable levels & they begin contracting again for new supplies. Based on SEC form 4, Paladin in particular is expected to be big winner in any new bull market, as it operates one of the lowest cost uranium mines in the world, the Langer Heinrich mine in Namibia, which was a fully producing mine before being idled in the last bear market. As such, it is a ready-to-go miner rather than a speculative prospect, and so is in a position to immediately capitalise on an uptick in uranium prices and a new contracting cycle with utilities. Given the extent of the structural supply/demand imbalance (which again wasn’t present during the previous bull market) combined with utilities likely becoming forced purchasers of uranium at almost any price, market commentators are forecasting the uranium spot price to reach highs of up to $150/lb, thus enabling the producers to contract at price levels 3x+ the current spot price, driving a massive increase in profitability and cash flows. With some very interesting dynamics and the sprott uranium trust acting as a catalyst, I think the uranium market has the potential to offer a really unique and asymmetric return over the next 2 years. To reproduce this analysis, use this guide on how to get stock price in Excel. You will also need high-quality stock data, I recommend you check out Finnhub Stock Api Cheers!

Using all stocks listed on the Japanese equity market and macroeconomic data for Japan, the dataset comprises the following series:

1. Japan_25_Portfolios_MV_PTBV: Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
2. Japan_25_Portfolios_MV_PE: Monthly returns for 25 size-PE portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
3. Japan_50_Portfolios_SECTOR: Monthly returns for 50 industry portfolios. (Raw data source: Datastream database)
4. Japan_3 Factors: Fama and French three-factors (RM, SMB and HML), following the Fama and French (1993) methodology. (Raw data source: Datastream database)
5. Japan_5 Factors: Fama and French five-factors (RM, SMB, HML, RMW, and CMA), following the Fama and French (2015) methodology. (Raw data source: Datastream database)
6. Japan_NUCLEAR_Y: Instrument in years with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
7. Japan_NUCLEAR_M: Instrument in months with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
8. Japan_RF_M: Three-month interest rate of the Treasury Bill for Japan. (Raw data source: OECD)
9. Company data: Names and general data of the companies that constitute the sample. (Raw data source: Datastream database)
10. Number of stocks in portfolios: Number of stocks included each year in Japan_25_Portfolios_MV_PTBV, Japan_25_Portfolios_MV_PE and Japan_50_Portfolios_SECTOR. (Raw data source: Datastream database)

We have produced all return series using the following data from Datastream: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), (iv) total assets (WC02999 series), (v) return on equity (WC08301 series), (vi) price-to-earnings ratio (PE series), and (vii) industry (SECTOR series). We have used the generic rules suggested by Griffin, Kelly, & Nardari (2010) for excluding non-common equity securities from Datastream data. We also exclude stocks with less than twelve observations. Accordingly, our sample comprises a total number of 5,212 stocks.

REFERENCES:

Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116, 1–22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277.

Nano Nuclear Energy price/book ratio from 2024 to 2025. Price/book ratio can be defined as

The North America Nuclear Power Plant and Equipment Market size was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, exhibiting a CAGR of 3.00">> 3.00 % during the forecasts periods.The market for nuclear power plants and equipment in North America encompasses all activities related to the construction, operation, and maintenance of nuclear facilities in the United States and Canada. Nuclear power is a crucial element of the region's energy landscape, providing a dependable source of baseload electricity generation that contributes significantly to energy security and efforts to reduce emissions. This market involves a comprehensive array of equipment and services essential for nuclear power plant operations, including reactors, turbines, generators, cooling systems, and supplies of nuclear fuel. In the United States, nuclear power plays a substantial role in electricity generation, particularly in states such as Illinois, Pennsylvania, and South Carolina, where nuclear plants are integral components of local economies and energy infrastructure. Canada also relies on nuclear energy, with Ontario being a prominent province with numerous nuclear reactors supplying power to the grid. Factors influencing the North American nuclear power plant and equipment market include regulatory frameworks, advancements in reactor technology (including small modular reactors, or SMRs), safety standards, and public perceptions regarding nuclear energy. The industry faces challenges such as the high initial costs associated with constructing new plants, concerns over waste management, and the need to decommission older reactors.Nevertheless, the market continues to progress through ongoing investments in advanced nuclear technologies, research into next-generation reactor designs, and efforts to extend the operational lifespans of existing facilities. Key drivers for this market are: 4., Increasing Demand for Natural Gas and Developing Gas Infrastructure 4.; Increasing Offshore Oil & Gas Exploration Activities. Potential restraints include: 4., Adoption of Cleaner Alternatives4.; High Volatility of Crude Oil Prices. Notable trends are: Pressurized Water Reactor (PWR) Type to Dominate the Market.

Global Nuclear Energy Market is poised for a significant growth, with market size projected to surge from USD 49.55 Billion in 2024 to USD 81.74 Billion by 2033, showcasing a robust Compound Annual Growth Rate (CAGR) of 5.72% during the forecast period.

The Global Nuclear Energy market size to cross USD 81.74 Billion by 2033. [https://edison.valuemarketresearch.com//uploads/report_images/VMR1121

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.

SMR - The Future of Nuclear Power?

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 uranium fuel core market is poised for significant growth, driven by the increasing demand for nuclear energy as a reliable and low-carbon power source. The resurgence of nuclear power in several countries, coupled with aging nuclear infrastructure requiring upgrades and replacements, is fueling this expansion. While regulatory hurdles and public perception remain challenges, advancements in reactor technology, including smaller modular reactors (SMRs), are mitigating these concerns and opening new market avenues. The market is segmented by application (nuclear energy, military, others) and type (enriched uranium dioxide, natural uranium dioxide), with nuclear energy dominating the application segment. Enriched uranium dioxide holds a larger share in the type segment due to its higher energy density. Geographically, North America and Europe currently hold substantial market share, but Asia-Pacific is projected to witness robust growth fueled by increasing energy demand and nuclear power plant construction in countries like China and India. Competition within the market is intense, with established players like Westinghouse Electric Company and Rosatom alongside emerging players continuously innovating and competing for market share. While fluctuating uranium prices and stringent safety regulations pose challenges, the long-term outlook for the uranium fuel core market remains positive, supported by the global push for clean energy solutions and stable government policies favoring nuclear power in many regions. The projected Compound Annual Growth Rate (CAGR) suggests a sustained expansion throughout the forecast period (2025-2033). This growth will likely be influenced by factors such as government investment in nuclear energy infrastructure, technological advancements in uranium enrichment and fuel fabrication, and the ongoing global energy transition. The market's growth trajectory will hinge on the successful deployment of new reactor technologies and a favorable regulatory environment. Furthermore, the successful management of spent nuclear fuel and the continuous advancement of safety measures are critical for sustaining the market’s growth. Continued investment in research and development, especially in areas such as accident-tolerant fuels and advanced reactor designs, will be essential for maintaining a competitive edge and driving further market expansion. The market is witnessing a gradual shift towards more efficient and safer fuel designs, leading to increased utilization of enriched uranium dioxide. However, the market’s susceptibility to global political instability and fluctuating uranium prices demands a comprehensive risk assessment and strategic planning by all market players.

Uranium fell to 77.40 USD/Lbs on July 3, 2025, down 0.51% from the previous day. Over the past month, Uranium's price has risen 8.40%, but it is still 9.63% lower than a year ago, 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 July of 2025.

The global uranium fuel rod market is experiencing robust growth, driven by the increasing demand for nuclear energy as a reliable and low-carbon electricity source. While concerns about nuclear waste disposal and safety remain, the urgency to mitigate climate change is pushing governments and energy companies to invest heavily in nuclear power infrastructure. This, coupled with the ongoing lifespan extensions of existing nuclear power plants, fuels the demand for uranium fuel rods. The market is segmented by application (nuclear energy, atomic bombs, others) and type (metal, ceramic, and dispersed nuclear fuel). Metal nuclear fuel currently dominates the market due to its established technology and widespread adoption, but ceramic and dispersed fuel types are expected to gain traction in the future due to their potential for improved efficiency and safety. Key players in the market include established multinational corporations like Areva S.A., Hitachi-GE Nuclear Energy, and Rosatom, alongside significant players from Asia such as China National Nuclear Corporation. Regional variations exist, with North America and Asia-Pacific expected to maintain significant market shares due to their existing nuclear power infrastructure and planned expansions. However, emerging economies in other regions are also showing increasing interest, leading to a more geographically diverse market in the coming years. The market's growth trajectory is influenced by several factors. Government policies supporting nuclear energy play a crucial role, as do advancements in fuel rod technology that enhance safety, efficiency, and reduce waste. Conversely, factors such as stringent regulations, fluctuating uranium prices, and public perception related to nuclear safety pose challenges to market expansion. However, the long-term outlook remains positive, driven by the need for clean energy solutions and technological improvements. While precise figures for market size and CAGR are unavailable, a reasonable estimate considering the industry trends indicates a steadily increasing market value over the forecast period (2025-2033), exceeding several billion dollars by the end of the forecast horizon. The growth is likely to be more pronounced during the early years of the forecast period and then moderate as the market matures.

Nano Nuclear Energy price to free cash flow ratio from 2024 to 2025. Price to free cash flow ratio can be defined as

The India nuclear power plant equipment market is segmented by Reactor Type (Pressurized Water Reactor, Pressurized Heavy Water Reactor, Other Reactor Types) and Carrier Type (Island Equipment, Auxiliary Equipment, and Research Reactor). The report offers the market size and forecasts for India nuclear power plant equipment (value in USD billion) for all the above segments.

In December 2024, the global average price per pound of uranium stood at roughly 60.22 U.S. dollars. Uranium prices peaked in June 2007, when it reached 136.22 U.S. dollars per pound. The average annual price of uranium in 2023 was 48.99 U.S. dollars per pound. Global uranium production Uranium is a heavy metal, and it is most commonly used as a nuclear fuel. Nevertheless, due to its high density, it is also used in the manufacturing of yacht keels and as a material for radiation shielding. Over the past 50 years, Kazakhstan and Uzbekistan together dominated uranium production worldwide. Uranium in the future Since uranium is used in the nuclear energy sector, demand has been constantly growing within the last years. Furthermore, the global recoverable resources of uranium increased between 2015 and 2021. Even though this may appear as sufficient to fulfill the increasing need for uranium, it was forecast that by 2035 the uranium demand will largely outpace the supply of this important metal.

The global enriched uranium market is poised for substantial growth, driven by the increasing demand for nuclear energy and military applications. While precise market size figures for 2025 are unavailable, leveraging industry reports and considering typical growth trajectories in established markets, we can estimate the 2025 market value to be around $15 billion USD. Assuming a conservative Compound Annual Growth Rate (CAGR) of 5% – a figure reflecting both anticipated nuclear power expansion and potential regulatory hurdles – the market is projected to reach approximately $22 billion USD by 2033. This growth is propelled by several key factors. Firstly, an increasing number of countries are investing in nuclear power plants to meet their energy demands and reduce carbon emissions. Secondly, the ongoing need for enriched uranium in military and defense applications provides a stable, albeit smaller, segment of the market. Thirdly, advancements in enrichment technologies and increased efficiency in uranium processing contribute to market expansion. However, constraints such as fluctuating uranium prices, stringent safety regulations, and concerns regarding nuclear waste disposal pose challenges to this growth. Market segmentation reveals that High Enriched Uranium (HEU), primarily used for military purposes, represents a smaller but significant portion of the market. Low Enriched Uranium (LEU), predominantly utilized in nuclear power plants, dominates the market share. Regionally, North America and Europe currently hold significant market shares, but the Asia-Pacific region is experiencing rapid growth, driven largely by China and India's expanding nuclear power programs. The competitive landscape is characterized by established players like Areva, Urenco, and Tenex, alongside significant contributions from national nuclear corporations like CNNC (China National Nuclear Corporation) and Orano (France). Future market dynamics will heavily depend on global energy policy shifts, advancements in nuclear technology, and the overall geopolitical climate, influencing both demand and supply within this vital sector.