The main stock market index of United States, the US500, rose to 6327 points on July 23, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.85% and is up 16.57% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

This dataset presents an extensive record of daily historical stock prices for Tesla, Inc. (TSLA), one of the world’s most innovative and closely watched electric vehicle and clean energy companies. The data was sourced from Yahoo Finance, a widely used and trusted provider of financial market data, and covers a significant period spanning from Tesla’s initial public offering (IPO) to the most recent date available at the time of extraction.

The dataset includes critical trading metrics for each market day, such as the opening price, highest and lowest prices of the day, closing price, adjusted closing price (accounting for dividends and splits), and total trading volume. This rich dataset supports a variety of use cases, including financial market analysis, investment research, time series forecasting, development and backtesting of trading algorithms, and educational projects in data science and finance.

Dataset Features

• Date: The calendar date for each trading session (in YYYY-MM-DD format)
• Open: The opening price of TSLA shares at the start of the trading day
• High: The highest price reached during the trading session
• Low: The lowest price reached during the trading session
• Close: The last price at which the stock traded during the day
• Adj Close: The closing price adjusted for corporate actions (splits, dividends, etc.)
• Volume: The total number of TSLA shares traded on that day

Source and Collection Details

• Source: Yahoo Finance - Tesla (TSLA) Historical Data
• Collection Method: Data was downloaded using Yahoo Finance's CSV export feature for accuracy and completeness.
• Time Range: Covers from Tesla’s IPO (June 2010) to the most recent available trading day.
• Data Integrity: Minimal cleaning was performed—dates were standardized, and any duplicate or empty rows were removed; all values remain as originally reported by Yahoo Finance.

Example Use Cases

• Stock Price Prediction: Train and test time series models (ARIMA, LSTM, Prophet, etc.) to forecast Tesla’s stock prices.
• Algorithmic Trading: Backtest and evaluate trading strategies using historical price and volume data.
• Market Trend Analysis: Analyze price trends, volatility, and return rates over different periods.
• Event Study: Investigate the impact of major announcements (e.g., product launches, earnings releases) on TSLA stock price.
• Educational Projects: Use as a hands-on resource for learning finance, statistics, or machine learning.

License & Acknowledgments

• Intended Use: This dataset is provided for academic, research, and personal projects. For commercial or investment use, please verify data accuracy and consult Yahoo Finance’s terms of use.
• Acknowledgment: Data sourced from Yahoo Finance. All trademarks and copyrights belong to their respective owners.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

Use our Stock Market dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

The latest closing stock price for Microsoft as of June 18, 2025 is 480.24. An investor who bought $1,000 worth of Microsoft stock at the IPO in 1986 would have $8,056,718 today, roughly 8,057 times their original investment - a 25.94% compound annual growth rate over 39 years. The all-time high Microsoft stock closing price was 480.24 on June 18, 2025. The Microsoft 52-week high stock price is 481.00, which is 0.2% above the current share price. The Microsoft 52-week low stock price is 344.79, which is 28.2% below the current share price. The average Microsoft stock price for the last 52 weeks is 422.77. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The main stock market index of United States, the US500, rose to 6369 points on July 24, 2025, gaining 0.16% from the previous session. Over the past month, the index has climbed 4.55% and is up 17.96% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Volatility of Stock Price Index for Oman (DDSM01OMA066NWDB) from 1992 to 2021 about Oman, volatility, stocks, price index, indexes, and price.

The latest closing stock price for Exxon as of June 27, 2025 is 109.38. An investor who bought $1,000 worth of Exxon stock at the IPO in 1984 would have $41,833 today, roughly 42 times their original investment - a 9.60% compound annual growth rate over 41 years. The all-time high Exxon stock closing price was 122.12 on October 07, 2024. The Exxon 52-week high stock price is 126.34, which is 15.5% above the current share price. The Exxon 52-week low stock price is 97.80, which is 10.6% below the current share price. The average Exxon stock price for the last 52 weeks is 112.58. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

The price of Meta (former Facebook) shares traded on the Nasdaq stock exchange fluctuated significantly but increased overall during the period from May 2012 to January 2025. After peaking at ****** U.S. dollars per share in August 2021, the price of Meta shares started to fluctuate and exceeded its previous peak in 2025. The share price stood at ****** U.S. dollars as of the end of January 2025. Substantial fluctuations in the last few years Meta's stock prices have fluctuated particularly after the rebranding announcement in late 2021. Following the announcement and through 2022, Meta's revenue remained rather stagnant, and its net income decreased considerably. Moreover, the tech giant announced one of the industry's largest layoffs in late 2022. As a result, the share price hit a low of ***** U.S. dollars in October 2022, the lowest value observed since 2016. However, Meta's share price has been steadily recovering since then. Shift in strategy for the world’s first social network Meta has shifted its focus to the metaverse, virtual reality (VR), and augmented reality (AR), with the rebranding in late 2021. As a result, Reality Labs was established as a dedicated business and research unit to focus on developing metaverse and AR/VR technologies. However, as of early 2023, Meta still relies mainly on advertising and its Family of Apps to generate most of its revenue, despite having made significant investments in virtual reality. Reality Labs generated *** billion U.S. dollars in revenue in 2024 and has been consistently incurring operating losses since 2019.

Graph and download economic data for Dow-Jones Industrial Stock Price Index for United States (M1109AUSM293NNBR) from Jan 1897 to Sep 1916 about stock market, industry, price index, indexes, price, and USA.

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Stock Analysis Software Market Size And Forecast

Stock Analysis Software Market size was valued at USD 145.6 Million in 2023 and is projected to reach USD 450.68 Million by 2031, growing at a CAGR of 15.17% during the forecast period 2024-2031.

Global Stock Analysis Software Market Drivers

The market drivers for the Stock Analysis Software Market can be influenced by various factors. These may include:

Growing Interest from Investors: As more people and organizations engage in the stock market, there is an increasing need for tools that help monitor and evaluate investments. Automation and Efficiency: Software adoption is fueled by traders' and investors' need for automated solutions that will expedite their analysis and decision-making. Data Accessibility: An abundance of financial data, such as current stock prices and corporate details, presents prospects for thorough analytical instruments. Advanced Technologies: Adding AI and machine learning to stock analysis software improves its capacity for prediction and provides more individualized insights, which draws in more users. Growth in Retail Trading: Individual investors' need for user-friendly stock analysis tools has been fueled by the growing acceptance of retail trading platforms. Regulatory Compliance: Software solutions that support compliance are in great demand as financial markets become more regulated. Cost-Effectiveness: By eliminating the need for human analysts, automated analysis systems can offer both individual and institutional investors a more affordable option. Cross-platform Integration: Users seeking coherent investing ecosystems will find stock research software more appealing if it interfaces with other financial tools and platforms. Global Market Expansion: Software that can assess equities across multiple locations and adhere to international regulations is needed as stock markets become increasingly global. User-Friendly Interfaces: The movement toward more user-friendly interfaces increases the accessibility of stock analysis software, which encourages non-professional investors to use it.

About this dataset

Stock market has become of the wonderful place to make money. Many loss and many gains. Many have tried to predict the price of a stock but fails miserably. Those who say they're able to do so, are the one who hide their biggest losses. If stock price cannot be determined by price alone, then there might be other way to predict it, or say to invest it in the "better" way. Otherwise Warren Buffet wouldn't as rich as he is now by luck alone. But who says we cannot play around with it and create our standard of investing in stock?

How to use this dataset

EDA RNN to predict future price Trend identifier Classifier Stock Recommendation

Features

Other Information

You also could use dataset outside this one. This dataset present all public company data in Indonesia. Might be helpful to do certain task, e.g. classification for the industry, etc.

Acknowledgement

Yahoo Finance

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

Stock market index in the USA, March, 2025 The most recent value is 182.06 points as of March 2025, a decline compared to the previous value of 187.78 points. Historically, the average for the USA from January 1960 to March 2025 is 44.99 points. The minimum of 2.98 points was recorded in June 1962, while the maximum of 187.78 points was reached in February 2025. | TheGlobalEconomy.com

The latest closing stock price for Bank Of America as of May 27, 2025 is 44.22. An investor who bought $1,000 worth of Bank Of America stock at the IPO in 1984 would have $30,631 today, roughly 31 times their original investment - a 8.79% compound annual growth rate over 41 years. The all-time high Bank Of America stock closing price was 47.44 on February 06, 2025. The Bank Of America 52-week high stock price is 48.08, which is 8.7% above the current share price. The Bank Of America 52-week low stock price is 33.06, which is 25.2% below the current share price. The average Bank Of America stock price for the last 52 weeks is 42.15. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The value of the DJIA index amounted to ****** at the end of June 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

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.

The Dow Jones U.S. Completion Total Stock Market Index

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

Historical data of the Taiwan Stock Exchange Weighted Index