Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

FinFeedAPI provides equity market data covering over 11,000 symbols, featuring historical T+1 data with an unlimited loopback period. We deliver everything from detailed trade records and multiple levels of order book depth (Level 1-3) to crucial regulatory and system messages.

Our data is engineered for performance, featuring nano-second precision timestamps. This ensures a competitive edge for high-frequency trading by enabling fair, accurate, and auditable transaction sequencing, critical for regulatory compliance. Access comprehensive equity market intelligence directly through our robust API offerings.

Why FinFeedAPI?

Market Coverage & Data Depth: - Historical Data: T+1 data on 11K+ symbols with unlimited historical lookback. - Trade Feeds: Detailed trade records including timestamps, sizes, prices, and conditions (e.g., odd lot, intermarket sweep, extended hours). - Level 1 Quotes: Best bid/ask prices, sizes, and timestamps. - Level 2 Price Book: Market depth with multiple bid/ask prices and aggregate order sizes. - Level 3 Order Book: The complete order book detailing individual orders.

Essential Messages: - Admin Messages: Trading status, official open/close prices, auction states, short sale restrictions, retail liquidity indicators, security directory. - System Events: Exchange-level notifications for key trading session phases.

Precision & Reliability: - Nano-second Timestamps: Ensuring fair, accurate, and auditable transaction sequencing for HFT and compliance. - Institutional Trust: Relied upon by financial institutions for dependable equity market information.

Financial institutions and trading firms rely on FinFeedAPI for mission-critical equity market intelligence. We are committed to delivering clean, precise, and comprehensive data when it matters most. If you require dependable and granular stock market data, FinFeedAPI provides the actionable insights you need.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Spain's main stock market index, the ES35, fell to 14009 points on July 11, 2025, losing 0.94% from the previous session. Over the past month, the index has declined 0.57%, though it remains 24.52% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Spain. Spain Stock Market Index (ES35) - values, historical data, forecasts and news - updated on July of 2025.

Prices for United States Stock Market Index (US500) including live quotes, historical charts and news. United States Stock Market Index (US500) was last updated by Trading Economics this July 11 of 2025.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Multiple and All Other Food Uses" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use in the South region on a monthly basis. Uses include "Bakery, Cereal and Related Products"; "Confectionery and Related Products"; "Ice Cream and Related Products"; "Beverages"; "Canned, Bottled and Frozen Foods"; "Multiple and All Other Food Uses", "Non-Food Uses", "Hotels, Restaurants and Institutions"; "Wholesale Grocers, Jobbers and Dealers", "Retail Grocers and Chain Stores", "Deliveries to Government Agencies", and "All Other Deliveries".

Cryptocurrency options markets have grown increasingly sophisticated, requiring reliable data infrastructure to support trading and analysis. Our platform gives you direct access to comprehensive crypto options data through straightforward API connections.

We capture the complete options chain across major crypto derivatives exchanges, delivering real-time and historical cryptocurrency market data that shows exactly what's happening in these complex markets. Each options contract is tracked with precision - strikes, expiration dates, premiums, open interest, and volume metrics all accessible through our standardized data feeds.

The data is available through multiple integration methods depending on your needs. Use our REST API for flexible queries and historical analysis, WebSocket for real-time market monitoring, or FIX protocol for institutional-grade connectivity with minimal latency.

Why work with us?

Market Coverage & Data Types: - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume

Technical Excellence: - 99% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

When options traders need reliable market intelligence, they don't leave it to chance. That's why trading desks across five continents, quantitative hedge funds managing billions, and fintech innovators building tomorrow's trading platforms all rely on our data infrastructure. We've established ourselves as a dependable source in a market where accuracy isn't just preferred - it's essential. While others promise comprehensive coverage, we deliver it consistently, trade after trade, day after day.

China's main stock market index, the SHANGHAI, rose to 3520 points on July 14, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.86% and is up 18.35% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use in the North Central region on a monthly basis. Uses include "Bakery, Cereal and Related Products"; "Confectionery and Related Products"; "Ice Cream and Related Products"; "Beverages"; "Canned, Bottled and Frozen Foods"; "Multiple and All Other Food Uses", "Non-Food Uses", "Hotels, Restaurants and Institutions"; "Wholesale Grocers, Jobbers and Dealers", "Retail Grocers and Chain Stores", "Deliveries to Government Agencies", and "All Other Deliveries".

NYMEX is a commodity futures exchange operating as part of the CME Group and primarily trades energy and metal contracts. NYMEX is known for trading futures contracts for crude oil, natural gas, heating oil, gasoline, and other energy products, as well as contracts for metals such as gold, silver, copper, and aluminum.

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.

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.

Context

Stock market data can be interesting to analyze and as a further incentive, strong predictive models can have large financial payoff. The amount of financial data on the web is seemingly endless. A large and well structured dataset on a wide array of companies can be hard to come by. Here I provide a dataset with historical stock prices (last 5 years) for all companies currently found on the S&P 500 index.

The script I used to acquire all of these .csv files can be found in this GitHub repository In the future if you wish for a more up to date dataset, this can be used to acquire new versions of the .csv files.

Content

The data is presented in a couple of formats to suit different individual's needs or computational limitations. I have included files containing 5 years of stock data (in the all_stocks_5yr.csv and corresponding folder) and a smaller version of the dataset (all_stocks_1yr.csv) with only the past year's stock data for those wishing to use something more manageable in size.

The folder individual_stocks_5yr contains files of data for individual stocks, labelled by their stock ticker name. The all_stocks_5yr.csv and all_stocks_1yr.csv contain this same data, presented in merged .csv files. Depending on the intended use (graphing, modelling etc.) the user may prefer one of these given formats.

All the files have the following columns: Date - in format: yy-mm-dd Open - price of the stock at market open (this is NYSE data so all in USD) High - Highest price reached in the day Low Close - Lowest price reached in the day Volume - Number of shares traded Name - the stock's ticker name

Acknowledgements

I scraped this data from Google finance using the python library 'pandas_datareader'. Special thanks to Kaggle, Github and The Market.

Inspiration

This dataset lends itself to a some very interesting visualizations. One can look at simple things like how prices change over time, graph an compare multiple stocks at once, or generate and graph new metrics from the data provided. From these data informative stock stats such as volatility and moving averages can be easily calculated. The million dollar question is: can you develop a model that can beat the market and allow you to make statistically informed trades!

Our extensive historical database captures every significant market movement, from the earliest Bitcoin trades through today's crypto ecosystem, across 350+ global exchanges.

This rich historical dataset serves multiple critical functions: from enabling sophisticated strategy backtesting and long-term trend analysis to supporting academic research and trading pattern identification. Whether analyzing market volatility, studying price correlations, or conducting deep market research, our historical data provides the reliable foundation needed for meaningful cryptocurrency market analysis.

Why work with us?

Market Coverage & Data Types: - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume - Full Cryptocurrency Investor Data

Technical Excellence: - 99,9% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

CoinAPI serves hundreds of institutions worldwide, from trading firms and hedge funds to research organizations and technology providers. Our commitment to data quality and technical excellence makes us the trusted choice for cryptocurrency market data needs.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities of stocks on a monthly basis.

The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

Israel's main stock market index, the TA-125, fell to 3121 points on July 10, 2025, losing 0.20% from the previous session. Over the past month, the index has climbed 13.30% and is up 51.70% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on July of 2025.

Access NYSE Arca Integrated market data feed for ETPs and ETFs with enhanced granularity and determinism not available via the SIPs or the Openbook feed.

NYSE Arca Integrated is a proprietary data feed that provides full order book updates, including every quote and order at each price level, on the Arca market (formerly ArcaEX, the Archipelago Exchange). It operates on NYSE's Pillar platform and disseminates all order book activity in an order-by-order view of events, including trade executions, order modifications, cancellations, and other book updates.

NYSE Arca is the leading US exchange for listing and trading exchange-traded funds (ETFs), offering the narrowest quoted spreads and maintaining the highest percentage of time (71.1%) at the NBBO for all U.S. ETFs. As of January 2025, it represented approximately 9.96% of the average daily volume (ADV) across all exchange-listed US securities, including those listed on Nasdaq, other NYSE venues, and Cboe exchanges.

With L3 granularity, NYSE Arca Integrated captures information beyond the L1, top-of-book data available through SIP feeds, enabling accurate modeling of book imbalances, quote lifetimes, and queue dynamics. This data includes explicit trade aggressor side, odd lots, and imbalances. Auction imbalances offer valuable insights into NYSE Arca’s opening and closing auctions by providing details like imbalance quantity, paired quantity, imbalance reference price, and book clearing price.

Full depth of book data on Arca is particularly valuable over the SIPs for modeling pre-market, after-market and sweep-to-fill liquidity on U.S. exchange-traded products (ETPs) and ETFs.

Historical data is available for usage-based rates or with any Databento US Equities subscription. Visit our pricing page for more details.

Asset class: Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, BBO-1s, BBO-1m, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance, Statistics, Status (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.