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.

Update

Unfortunately, the API this dataset used to pull the stock data isn't free anymore. Instead of having this auto-updating, I dropped the last version of the data files in here, so at least the historic data is still usable.

Content

This dataset provides free end of day data for all stocks currently in the Dow Jones Industrial Average. For each of the 30 components of the index, there is one CSV file named by the stock's symbol (e.g. AAPL for Apple). Each file provides historically adjusted market-wide data (daily, max. 5 years back). See here for description of the columns: https://iextrading.com/developer/docs/#chart

Since this dataset uses remote URLs as files, it is automatically updated daily by the Kaggle platform and automatically represents the latest data.

Acknowledgements

List of stocks and symbols as per https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

Thanks to https://iextrading.com for providing this data for free!

Terms of Use

Data provided for free by IEX. View IEX’s Terms of Use.

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.

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)

Sources

The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.

The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.

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.

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This dataset contains historical stock data for CVS Health, including daily opening and closing prices, highest and lowest prices of the day, adjusted closing prices, and trading volume.

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Columns Information

Date

• Description: The specific day the stock data was recorded.
• Data Type: Date (Format: YYYY-MM-DD)

Open

• Description: The price at which the stock started trading when the market opened.
• Data Type: Numeric (Format: USD)

High

• Description: The highest price at which the stock traded during the day.
• Data Type: Numeric (Format: USD)

Low

• Description: The lowest price at which the stock traded during the day.
• Data Type: Numeric (Format: USD)

Close

• Description: The price at which the stock ended trading when the market closed.
• Data Type: Numeric (Format: USD)

Adj Close

• Description: The closing price adjusted for dividends and stock splits.
• Data Type: Numeric (Format: USD)

Volume

• Description: The total volume of shares traded during the day.
• Data Type: Integer

The dataset provides valuable insights into the stock performance of CVS Health over time, starting from February 22, 1973.

The Dow Jones Industrial Average (DJIA) is a stock market index used to analyze trends in the stock market. While many economists prefer to use other, market-weighted indices (the DJIA is price-weighted) as they are perceived to be more representative of the overall market, the Dow Jones remains one of the most commonly-used indices today, and its longevity allows for historical events and long-term trends to be analyzed over extended periods of time. Average changes in yearly closing prices, for example, shows how markets developed year on year. Figures were more sporadic in early years, but the impact of major events can be observed throughout. For example, the occasions where a decrease of more than 25 percent was observed each coincided with a major recession; these include the Post-WWI Recession in 1920, the Great Depression in 1929, the Recession of 1937-38, the 1973-75 Recession, and the Great Recession in 2008.

Silver rose to 47.97 USD/t.oz on October 3, 2025, up 2.08% from the previous day. Over the past month, Silver's price has risen 17.95%, and is up 49.05% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on October of 2025.

Natural gas fell to 3.33 USD/MMBtu on October 3, 2025, down 3.18% from the previous day. Over the past month, Natural gas's price has risen 8.41%, and is up 16.76% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on October of 2025.

Free historical options data, dataset files in CSV format.

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Brent rose to 64.35 USD/Bbl on October 3, 2025, up 0.37% from the previous day. Over the past month, Brent's price has fallen 3.94%, and is down 17.55% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Brent crude oil - values, historical data, forecasts and news - updated on October of 2025.

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Finnhub is the ultimate stock api in the market, providing real-time and historical price for global stocks with Rest API and websocket. We also support a tons of other financial data like stock fundamentals, analyst estimates, fundamental data and more. Download the file to access balance sheet of Amazon.

The Netflix Stock Price Dataset provides historical trading data including date, opening, high, low, closing, adjusted closing prices, and trading volume. It is ideal for financial analysis, forecasting, and machine learning applications.

STOCK narxlar tarixini kuzatish kriptovalyuta investorlariga o'z investitsiyalari samaradorligini osongina kuzatish imkonini beradi. Vaqt o'tishi bilan STOCK uchun ochilish qiymati, yuqori va yopilishini hamda savdo hajmini qulay tarzda kuzatishingiz mumkin. Bundan tashqari, siz kunlik o'zgarishlarni bir zumda foiz sifatida ko'rishingiz mumkin, bu esa sezilarli tebranishlar bo'lgan kunlarni aniqlashni osonlashtiradi. Bizning STOCK narxlari tarixiy ma'lumotlariga ko'ra, uning qiymati 2025-10-04da misli ko'rilmagan cho'qqigacha ko'tarilib, -- AQSh dollaridan oshib ketdi. Boshqa tomondan, STOCK narxlari traektoriyasidagi eng past nuqta, odatda “STOCK barcha vaqtlardagi eng past” deb ataladigan nuqta 2025-10-04 da sodir bo'ldi. Agar kimdir shu vaqt ichida STOCK xarid qilgan bo'lsa, u hozirda 0% miqdorida ajoyib foyda olishi mumkin edi. Maqsadga ko'ra 999,987,687.77 STOCK yaratiladi. Hozirda STOCK aylanma ta'minoti taxminan 999,987,700 ni tashkil qiladi. Ushbu sahifada keltirilgan barcha narxlar ishonchli manba Bitgetdan olingan. Investitsiyalaringizni tekshirish uchun bitta manbaga tayanish juda muhim, chunki qiymatlar turli sotuvchilar orasida farq qilishi mumkin. Tarixiy STOCK narxlari ma'lumotlar to'plamimiz 1 daqiqa, 1 kun, 1 hafta va 1 oy oralig'idagi ma'lumotlarni o'z ichiga oladi (ochiq/yuqori/past/yopiq/hajm). Ushbu ma'lumotlar to'plamlari izchillik, to'liqlik va aniqlikni ta'minlash uchun qattiq sinovdan o'tkazildi. Ular maxsus savdo simulyatsiyasi va test sinovlari uchun mo'ljallangan bo'lib, ularni bepul yuklab olish mumkin va real vaqt rejimida yangilanadi.

Graph and download economic data for NASDAQ Composite Index (NASDAQCOM) from 1971-02-05 to 2025-10-03 about composite, NASDAQ, stock market, indexes, and USA.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-10-05 to 2025-10-03 about stock market, average, industry, and USA.