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.

The main stock market index of United States, the US500, rose to 6159 points on June 27, 2025, gaining 0.30% from the previous session. Over the past month, the index has climbed 4.60% and is up 12.80% 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 June of 2025.

Use our Stock prices 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.

Dataset Information

This dataset includes daily price data for various stocks.

  Instruments Included

7000+ US Stocks

  Dataset Columns

symbol: The symbol of the stock. date: The date of the data. open: The opening price of the stock. high: The highest price of the stock. low: The lowest price of the stock. close: The closing price of the stock. volume: The volume of the stock. adj_close: The adjusted closing price of the stock.

  Data Splits

The… See the full description on the dataset page: https://huggingface.co/datasets/paperswithbacktest/Stocks-Daily-Price.

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.

Bermuda's main stock market index, the BSX, rose to 2839 points on June 26, 2025, gaining 0.04% from the previous session. Over the past month, the index has climbed 2.17% and is up 17.63% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Bermuda. Bermuda Stock Exchange Index - values, historical data, forecasts and news - updated on June of 2025.

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.

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.

The latest closing stock price for Marathon Petroleum as of June 17, 2025 is 170.08. An investor who bought $1,000 worth of Marathon Petroleum stock at the IPO in 2011 would have $12,079 today, roughly 12 times their original investment - a 20.16% compound annual growth rate over 14 years. The all-time high Marathon Petroleum stock closing price was 213.36 on April 05, 2024. The Marathon Petroleum 52-week high stock price is 183.31, which is 7.8% above the current share price. The Marathon Petroleum 52-week low stock price is 115.10, which is 32.3% below the current share price. The average Marathon Petroleum stock price for the last 52 weeks is 155.18. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Description

This dataset provides detailed stock price data for IBM and Oracle over a 20-year period from January 2004, to January, 2024. This dataset contains historical stock data for Oracle Corporation (ORCL) and International Business Machines Corporation (IBM). This comprehensive dataset is ideal for financial analysis, investment research, and time series forecasting. The data is recorded at a 5-day interval, offering a comprehensive view of the stock performance of these two technology giants.

Data Overview

The dataset includes the following columns: - Date: The date of the stock price record. - Open: The opening price of the stock on that date. - High: The highest price of the stock on that date. - Low: The lowest price of the stock on that date. - Close: The closing price of the stock on that date. - Adj Close: The adjusted closing price of the stock on that date, accounting for corporate actions. - Volume: The number of shares traded on that date. - Stock: The ticker symbol (IBM or ORCL) indicating which company's stock data is represented.

Use Cases

This dataset is ideal for: - Financial Analysis: Conducting historical performance analysis of IBM and Oracle stocks. - Machine Learning: Training models for stock price prediction. - Comparative Studies: Comparing the market behavior and trends of IBM and Oracle over two decades. - Investment Strategies: Backtesting investment strategies using historical data.

Data Source

The stock data was fetched using the Yahoo Finance API through the yfinance library in Python.

New York Stock Exchange: Index: Dow Jones US Mid Cap Index data was reported at 1,823.120 NA in Apr 2025. This records an increase from the previous number of 1,820.520 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Mid Cap Index data is updated monthly, averaging 1,821.820 NA from Mar 2024 (Median) to Apr 2025, with 14 observations. The data reached an all-time high of 1,987.270 NA in Nov 2024 and a record low of 1,678.780 NA in Apr 2024. New York Stock Exchange: Index: Dow Jones US Mid Cap Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.

This statistic shows the stock prices of selected oil and gas commodities from January 2, 2020 to February 4, 2025. After the Russian invasion of Ukraine in February 2022, energy prices climbed significantly. The highest increase can be observed for natural gas, whose price peaked in August and September 2022. By the beginning of 2023, natural gas price started to decline.

This statistic shows the total trading value of stocks on Taiwan Stock Exchange market from 2013 to 2023. In 2023, the total stock trading value on Taiwan Stock Exchange market reached around 63 trillion New Taiwan dollars.

Description: This dataset contains 24 years of historical stock data for ITC Limited, a leading Indian multinational conglomerate engaged in businesses such as FMCG (Fast-Moving Consumer Goods), hotels, paperboards, and agri-business. The data spans from [start year] to [end year] and includes daily stock metrics such as opening price, closing price, high, low, volume, and more, providing a comprehensive view of ITC's performance in the National Stock Exchange (NSE).

Context: The dataset offers valuable insights into the long-term trends, volatility, and trading patterns of ITC stocks, facilitating quantitative analysis and investment research. Researchers, analysts, and investors can leverage this dataset to conduct historical performance analysis, develop trading strategies, and make informed investment decisions related to ITC Limited.

Sources: The dataset is sourced from reliable financial data providers and publicly available stock market archives. The data undergoes rigorous validation and cleaning processes to ensure accuracy and consistency, providing users with reliable information for their analyses.

Inspiration: The creation of this dataset was inspired by the growing interest in quantitative finance, stock market analysis, and algorithmic trading within the data science community. By making this dataset available on platforms like Kaggle, we aim to empower researchers, data scientists, and enthusiasts to explore the dynamics of ITC's stock performance and contribute to the advancement of financial analytics and investment strategies.

On January 30, 2025, the index closed at 52,050 points. The IPC Mexico (Índice de Precios y Cotizaciones) is the benchmark stock market index of the Bolsa Mexicana de Valores (BMV), representing the performance of the most liquid and capitalized companies listed on the Mexican stock exchange, and it currently includes 35 companies. Mexico's IPC stock exchange index was impacted by the coronavirus (COVID-19) pandemic in 2020, but had recovered to pre-pandemic levels by early 2021. As of October 15, 2020, the stock market was still affected by the uncertainty and instability that the pandemic brought, with a value amounting to 38,059 points. However, in April 2021, Mexico's IPC stock market index reached figures prior to the pandemic.

The Predictive AI in Stock Market is estimated to reach USD 4,100.6 Mn By 2034, Riding on a Strong 17.3% CAGR throughout the forecast period.

Ecuador's main stock market index, the Ecuador General, fell to 1239 points on June 20, 2025, losing 0.09% from the previous session. Over the past month, the index has declined 2.10%, though it remains 7.89% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Ecuador. Ecuador General Index - values, historical data, forecasts and news - updated on June of 2025.

This table contains 25 series, with data for years 1956 - present (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Toronto Stock Exchange Statistics (25 items: Standard and Poor's/Toronto Stock Exchange Composite Index; high; Standard and Poor's/Toronto Stock Exchange Composite Index; close; Toronto Stock Exchange; oil and gas; closing quotations; Standard and Poor's/Toronto Stock Exchange Composite Index; low ...).

The price of Intel shares traded on the Nasdaq stock exchange fluctuated significantly during the period between January 2010 and December 2024. The price of Intel share stood at 20.05 U.S. dollar as of the end of December 2024, significantly lower than the previous month.

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