Nvidia reported $46.74B in Sales Revenues for its fiscal quarter ending in June of 2025. Data for Nvidia | NVDA - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last October in 2025.

1. Overview

This dataset provides monthly stock price data for the MAG7 over the past 20 years (2004–2024). The data includes key financial metrics such as opening price, closing price, highest and lowest prices, trading volume, and percentage change. The dataset is valuable for financial analysis, stock trend forecasting, and portfolio optimization.

2. What is MAG7 ?

MAG7 refers to the seven largest and most influential technology companies in the U.S. stock market : - Microsoft (MSFT) - Apple (AAPL) - Google (Alphabet, GOOGL) - Amazon (AMZN) - Nvidia (NVDA) - Meta (META) - Tesla (TSLA)

These companies are known for their market dominance, technological innovation, and significant impact on global stock indices such as the S&P 500 and Nasdaq-100.

3. Dataset Details

The dataset consists of historical monthly stock prices of MAG7, retrieved from Investing.com. It provides an overview of how these stocks have performed over two decades, reflecting market trends, economic cycles, and technological shifts.

4. Columns Descriptions

• Date The recorded month and year (DD-MM-YYYY)
• Price The closing price of the stock at the end of the month
• Open The price at which the stock opened at the beginning of the month
• High The highest stock price recorded in the month
• Low The lowest stock price recorded in the month
• Vol. The total trading volume for the month
• Change % The percentage change in stock price compared to the previous month # 5. Data Source & Format The dataset was obtained from Investing.com and downloaded in CSV format. The data has been processed to ensure consistency and accuracy, with date formats standardized for time-series analysis. # 6. Potential Use Cases This dataset can be used for :
• 📈 Stock price trend analysis over 20 years
• 📊 Building financial models for long-term investing
• 🔎 Machine learning applications in stock market prediction
• 📉 Evaluating market volatility and economic impact on MAG7 stocks

7. Limitations & Considerations

• ⚠️ The dataset is limited to monthly data, meaning short-term price fluctuations are not captured.
• ⚠️ Trading volume (Vol.) may vary in availability due to differences in reporting.
• ⚠️ External factors such as stock splits, dividends, and market crashes are not explicitly noted but may impact historical trends.

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.

Nvidia Stock Hits All-Time High: What's Driving the Bull Run?

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

Japan's main stock market index, the JP225, fell to 47582 points on October 17, 2025, losing 1.44% from the previous session. Over the past month, the index has climbed 5.03% and is up 22.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on October 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.

NVIDIA: Still a Wise Investment? (NVDA)

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

ABOUT SAP:

Headquartered in Walldorf, Germany, SAP is the market leader in enterprise application software. Founded in 1972, SAP (which stands for "Systems, Applications, and Products in Data Processing") has a rich history of innovation and growth as a true industry leader.

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ABOUT DATASET:

This dataset contains detailed historical stock price data for SAP, covering the period from 09/22/1995 to 06/14/2024. The data is collected from Yahoo Finance and includes daily records of the stock's opening price, highest price, lowest price, closing price, and trading volume. Each entry in the dataset represents a single trading day, providing a comprehensive view of the stock's price movements and market activity.

PURPOSE OF DATASET

The purpose of this dataset is to provide analysts, traders, and researchers with accurate and granular historical stock price data for SAP. This data can be used for various applications, including:

• Technical Analysis: Identify trends and patterns in the stock's price movements. Calculate technical indicators such as moving averages, RSI, and Bollinger Bands.

• Market Sentiment Analysis: Analyze how the stock's price responds to market events and news. Compare the opening and closing prices to understand daily sentiment.

• Algorithmic Trading: Develop and test trading algorithms based on historical price and volume data. Use past price movements to simulate trading strategies.

• Predictive Modeling: Build models to forecast future prices and trading volumes. Use historical data to identify potential price movements and market trends.

• Educational Purposes: Serve as a teaching tool for financial education. Help students and researchers understand the dynamics of stock price changes and market behavior.

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this dataset offers a solid foundation for a wide range of financial analyses and trading applications.

Le suivi de l'historique des prix NVIDIA tokenized stock (xStock) permet aux investisseurs crypto de suivre facilement les performances de leur investissement. Vous pouvez facilement suivre le prix d'ouverture, le prix haut et le prix de clôture de NVIDIA tokenized stock (xStock) au fil du temps, ainsi que le volume de trading. En outre, vous pouvez instantanément visualiser la variation quotidienne en pourcentage, ce qui vous permet d'identifier facilement les jours où les fluctuations sont importantes. D'après l'historique des prix NVIDIA tokenized stock (xStock), sa valeur a atteint un sommet sans précédent en 2025-10-10, dépassant $195.71 $. D'autre part, le point le plus bas de la trajectoire du prix de NVIDIA tokenized stock (xStock), communément appelé "plus bas niveau historique NVIDIA tokenized stock (xStock)", s'est produit le 2025-07-02. Si vous aviez acheté des NVIDIA tokenized stock (xStock) pendant cette période, vous bénéficieriez actuellement d'un profit remarquable de 23%. 60,453.86 NVIDIA tokenized stock (xStock) seront créés automatiquement. À l'heure actuelle, l'offre en circulation de NVIDIA tokenized stock (xStock) est d'environ 60,453.86. Tous les prix indiqués sur cette page ont été obtenus auprès de Bitget, une source fiable. Il est essentiel de se fier à une seule source pour vérifier vos investissements, car les valeurs peuvent varier d'un vendeur à l'autre. Notre ensemble de données historiques NVIDIA tokenized stock (xStock) comprend des données à intervalles de 1 minute, 1 jour, 1 semaine et 1 mois (prix d'ouverture/haut/bas/clôture/volume). Ces ensembles de données ont fait l'objet de tests rigoureux afin d'en garantir la cohérence, l'exhaustivité et l'exactitude. Ils sont spécialement conçus pour les simulations de trading et le backtesting, peuvent être téléchargés gratuitement et sont mis à jour en temps réel.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

When comparing the data segment revenues of Nvidia, AMD, and Intel, it is clear that Nvidia has experienced extraordinary growth. In the second quarter of the 2025 calendar year, Nvidia generated 41.1 billion U.S. dollars through its data center segment, a part of the business that includes graphics processing unit (GPU) sales. GPUs are used to train and run various large language models, most notably ChatGPT, the one developed by OpenAI.

Nemotron NVIDIA Companion Ang pagsubaybay sa kasaysayan ng presyo ay nagbibigay-daan sa mga crypto investor na madaling masubaybayan ang performance ng kanilang pamumuhunan. Maginhawa mong masusubaybayan ang opening value, high, at close sa Nemotron NVIDIA Companion sa paglipas ng panahon, pati na rin ang trade volume. Bukod pa rito, maaari mong agad na tingnan ang pang-araw-araw na pagbabago bilang isang porsyento, na ginagawang effortless na tukuyin ang mga araw na may significant fluctuations. Ayon sa aming data ng history ng presyo ng Nemotron NVIDIA Companion, tumaas ang halaga nito sa hindi pa naganap na peak sa 2025-10-19, na lumampas sa -- USD. Sa kabilang banda, ang pinakamababang punto sa trajectory ng presyo ni Nemotron NVIDIA Companion, na karaniwang tinutukoy bilang "Nemotron NVIDIA Companion all-time low", ay naganap noong 2025-10-19. Kung ang isa ay bumili ng Nemotron NVIDIA Companion sa panahong iyon, kasalukuyan silang masisiyahan sa isang kahanga-hangang kita na 0%. Sa pamamagitan ng disenyo, ang 999,362,702.39 Nemotron NVIDIA Companion ay malilikha. Sa ngayon, ang circulating supply ng Nemotron NVIDIA Companion ay tinatayang 999,362,700. Ang lahat ng mga presyong nakalista sa pahinang ito ay nakuha mula sa Bitget, galing sa isang reliable source. Napakahalagang umasa sa iisang pinagmulan upang suriin ang iyong mga investment, dahil maaaring mag-iba ang mga halaga sa iba't ibang nagbebenta. Kasama sa aming makasaysayang Nemotron NVIDIA Companion dataset ng presyo ang data sa pagitan ng 1 minuto, 1 araw, 1 linggo, at 1 buwan (bukas/mataas/mababa/close/volume). Ang mga dataset na ito ay sumailalim sa mahigpit na pagsubok upang matiyak ang consistency, pagkakumpleto, at accurancy. Ang mga ito ay partikular na idinisenyo para sa trade simulation at mga layunin ng backtesting, madaling magagamit para sa libreng pag-download, at na-update sa real-time.

O rastreamento do histórico de preços de Nemotron NVIDIA Companion permite que os investidores em criptomoedas monitorem facilmente o desempenho de seus investimentos. Você pode acompanhar de forma conveniente o valor de abertura, a máxima e o fechamento de Nemotron NVIDIA Companion ao longo do tempo, bem como o volume de trading. Além disso, você pode visualizar instantaneamente a variação diária como porcentagem, o que facilita a identificação de dias com flutuações significativas. De acordo com nossos dados do histórico de preço de Nemotron NVIDIA Companion, seu valor subiu para um pico sem precedentes em 2025-10-20, ultrapassando -- USD. Por outro lado, o ponto mais baixo na trajetória de preços de Nemotron NVIDIA Companion, comumente chamado de "mínima histórica de Nemotron NVIDIA Companion", ocorreu em 2025-10-20. Se alguém tivesse comprado Nemotron NVIDIA Companion durante esse período, teria atualmente um lucro notável de 0%. Por padrão, 999,362,702.39 Nemotron NVIDIA Companion será criado. No momento, a oferta circulante de Nemotron NVIDIA Companion é de aproximadamente 999,362,700. Todos os preços listados nesta página foram obtidos na Bitget, uma fonte confiável. É fundamental confiar em uma única fonte para verificar seus investimentos, pois os valores podem variar entre diferentes vendedores. Nosso conjunto de dados históricos de preços de Nemotron NVIDIA Companion inclui dados em intervalos de 1 minuto, 1 dia, 1 semana e 1 mês (abertura/máxima/mínima/fechamento/volume). Esses conjuntos de dados foram submetidos a testes rigorosos para garantir a consistência, a integridade e a precisão. Eles são projetados especificamente para fins de simulação de trading e backtesting, prontamente disponíveis para download gratuito e atualizados em tempo real.

El principal índice bursátil de Estados Unidos, el US500, subió a 6690 puntos el 20 de octubre de 2025, ganando un 0,39% con respecto a la sesión anterior. Durante el último mes, el índice ha descendido un 0,06%, aunque sigue siendo un 14,28% más alto que hace un año, según la negociación en un contrato por diferencia (CFD) que sigue este índice de referencia de Estados Unidos. Los valores actuales, los datos históricos, las previsiones, estadísticas, gráficas y calendario económico - Estados Unidos - Mercado de acciones.