Nuclear Energy Index rose to 42.06 USD on September 10, 2025, up 0.29% from the previous day. Over the past month, Nuclear Energy Index's price has risen 6.08%, and is up 65.59% 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 September 9 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.

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

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.

Societatea Nationala Nuclearelectrica 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.

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

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!

Uranium fell to 76.75 USD/Lbs on September 9, 2025, down 0.26% from the previous day. Over the past month, Uranium's price has risen 6.30%, but it is still 3.46% 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 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.

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

Non-irradiated fuel elements made up almost ** percent of South Korea's trade value gained from nuclear reactor parts in 2022. According to the source, the export value of nuclear reactors from South Korea decreased from 2020 to 2021.

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.

Stock Price Time Series for Fluor Corporation. Fluor Corporation provides engineering, procurement, and construction (EPC); fabrication and modularization; and project management services worldwide. The company operates through three segments: Urban Solutions, Energy Solutions, and Mission Solutions. The Urban Solutions segment offers EPC and project management services to the advanced technologies and manufacturing, life sciences, mining and metals, and infrastructure industries. This segment also provides professional staffing services to the company and third-party clients with technical, professional, and craft resources on a contract or permanent placement basis. The Energy Solutions segment offers EPC services for traditional oil and gas markets, including the production and fuels, chemicals, LNG, and power markets. This segment also provides solutions to the energy transition markets, including nuclear power and other low-carbon energy sources, asset decarbonization, carbon capture, renewable fuels, waste-to-energy, green chemicals, and hydrogen; and consulting services, such as feasibility studies, process assessments, and project finance structuring. The Mission Solutions segment offers technical solutions to the U.S. and other governments. This segment provides site management, environmental remediation, and decommissioning for nuclear remediation at governmental facilities, as well as services to commercial nuclear clients. It also delivers solutions for nuclear security and operation, nuclear waste management, and laboratory management; and operation and maintenance, logistics, EPC, and life support solutions for mission-critical facilities across U.S. military service organizations. The company was founded in 1912 and is headquartered in Irving, Texas.

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

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.

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

The global Uranium Dioxide Fuel Pellets market is experiencing robust growth, driven by the increasing demand for nuclear energy as a reliable and low-carbon power source. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033, reaching an estimated value of $4.2 billion by 2033. This growth is fueled by several factors, including the ongoing expansion of existing nuclear power plants and the construction of new facilities, particularly in Asia-Pacific and emerging economies. Government policies supporting nuclear energy as a clean energy alternative further contribute to the market's expansion. However, the market faces certain restraints, including concerns about nuclear waste disposal and safety, as well as fluctuating uranium prices. Segmentation reveals a significant portion of the market is driven by the Light Water Reactor (LWR) application, with an increasing adoption of advanced reactor technologies anticipated in the coming years. Key players in the market, such as Areva S.A., Hitachi-GE Nuclear Energy, and Westinghouse Electric Company LLC, are constantly innovating to improve pellet performance and efficiency, driving competition and further market growth. The regional breakdown shows a significant market share held by North America and Europe, driven by the established nuclear power infrastructure in these regions. However, Asia Pacific is projected to demonstrate the highest growth rate over the forecast period due to increasing energy demands and government initiatives supporting nuclear power development. While specific market shares for each region are not explicitly provided, it's reasonable to infer a larger share for North America and Europe initially, with a progressive shift towards a larger share for the Asia-Pacific region as their nuclear power infrastructure expands. This is supported by the ongoing construction of new nuclear plants in several Asian countries. Continued advancements in fuel pellet technology and the overall need for clean and reliable energy will be pivotal for sustaining this market expansion.

Stock Price Time Series for Huntington Ingalls Industries Inc. Huntington Ingalls Industries, Inc. designs, builds, overhauls, and repairs military ships in the United States. It operates through three segments: Ingalls, Newport News, and Mission Technologies. The company is involved in the design and construction of non-nuclear ships comprising amphibious assault ships; expeditionary warfare ships; surface combatants; and national security cutters for the U.S. Navy and U.S. Coast Guard. It also provides nuclear-powered ships, such as aircraft carriers and submarines, as well as refueling and overhaul, and inactivation services of nuclear-powered aircraft carriers. In addition, the company offers naval nuclear support services, including fleet services comprising design, construction, maintenance, and disposal activities for in-service the U.S. Navy nuclear ships; and maintenance services on nuclear reactor prototypes. Further, the company provides C5ISR systems and operations; application of artificial intelligence and machine learning to battlefield decisions; defensive and offensive cyberspace strategies and electronic warfare; uncrewed autonomous systems; live, virtual, and constructive solutions; and fleet sustainment; and critical nuclear operations. Huntington Ingalls Industries, Inc. was founded in 1886 and is headquartered in Newport News, Virginia.

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.

Stock Price Time Series for Public Service Enterprise Group Inc. Public Service Enterprise Group Incorporated, through its subsidiaries, operates in electric and gas utility, and nuclear generation businesses in the United States. It operates through PSE&G and PSEG Power segments. The PSE&G segment transmits electricity; distributes electricity and natural gas to residential, commercial, and industrial customers; and appliance services and repairs to customers through its service territory, as well as invests in solar generation projects, and energy efficiency and related programs. The PSEG Power segment engages in nuclear generation businesses; and supplies power and natural gas to nuclear power plants and gas storage facilities activities. As of December 31, 2024, it had electric transmission and distribution system of 25,000 circuit miles and 869,000 poles; 57 switching stations with an installed capacity of 40,000 megavolt-amperes (MVA), and 234 substations with an installed capacity of 10,750 MVA; four electric distribution headquarters and five electric sub-headquarters; 18,000 miles of gas mains, 12 gas distribution headquarters, two sub-headquarters, and two meter shop, as well as 54 natural gas metering and regulating stations; and 158 MegaWatts defined conditions of installed PV solar capacity. Public Service Enterprise Group Incorporated was founded in 1903 and is based in Newark, New Jersey.