Full historical data for the S&P 500 (ticker ^GSPC), sourced from Yahoo Finance (https://finance.yahoo.com/).

Including Open, High, Low and Close prices in USD + daily volumes.

Info about S&P 500: https://en.wikipedia.org/wiki/S%26P_500

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.

This dataset contains the full historical record of the S&P 500 index (^GSPC), downloaded via the Yahoo Finance API using the yfinance Python library.

The dataset includes: - Date: Trading date - Open, High, Low, Close: Daily price levels - Volume: Daily trading volume

Period covered: Dec 30, 1927 – Aug 31, 2025 Frequency: Daily

⚠️ Disclaimer: This dataset is provided for educational and research purposes only. Redistribution or commercial use may be subject to Yahoo Finance’s Terms of Service

License

Data sourced from Yahoo Finance. Provided for educational and research purposes only. Redistribution may be restricted.

View monthly updates and historical trends for S&P 500 2 Year Return. from United States. Source: Standard and Poor's. Track economic data with YCharts an…

Context

Stock market data can be interesting to analyze, 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 view a dataset with historical stock prices for all companies on the S&P 500 index.

Content

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 - lowest price reached in the day

Close - close price

Volume - number of shares traded

Acknowledgements

Thanks to Kaggle, Github, yahoo finance.

Purpose of creating the dataset

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. And people can build quantitative models such as: build portfoio, predict volatility, arbitrage, trading strategies.

S&P 500 - Historical chart and current data through 2025.

The dataset comprises historical stock price and trading volume data from S&P 500 component stocks over a period of about 10 years (from 01/02/2009 to 12/24/2018), used to evaluate the proposed Mid-LSTM stock prediction model.

View monthly updates and historical trends for S&P 500. from United States. Source: Standard and Poor's. Track economic data with YCharts analytics.

United States - S&P 500 was 6812.63000 Index in December of 2025, according to the United States Federal Reserve. Historically, United States - S&P 500 reached a record high of 6890.89000 in October of 2025 and a record low of 676.53000 in March of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - S&P 500 - last updated from the United States Federal Reserve on December of 2025.

Historical dataset of the United States Stock Market Index (S&P 500), covering values from 1928-01-01 to 2025-11-28, with the latest releases and long-term trends. Available for free download in CSV format.

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 December 1 of 2025.

S&P 500 Stock Prices

Historical stock market data for current S&P 500 companies, from 2014-2017. Each record represents a single day of trading, and includes the ticker name, volume, high, low, open and close prices.

Recommended Analysis

Which date in the sample saw the largest overall trading volume? On that date, which two stocks were traded most?

On which day of the week does volume tend to be highest? Lowest?

On which date did Amazon (AMZN) see the most volatility, measured by the difference between the high and low price?

If you could go back in time and invest in one stock from 1/2/2014 - 12/29/2017, which would you choose? What % gain would you realize?

This dataset provides a comprehensive collection of historical stock data for all the companies listed on the S&P 500 index. It includes details such as daily open, close, high, low prices, and volume for each listed company. The dataset is intended to help researchers, investors, and data scientists gain insights into the performance of these companies and explore trends, patterns, or anomalies in the stock market.

The S&P 500 index dropped significantly between January 3 and September 9, 2022. As of January 3, the index stood at ******** points, and it dropped approximately 15 percent by September 2022. In August 2025, the daily value of the S&P 500 increased over 6**** points and reached ********as of August 19 of the same year.

1) Data Introduction • The S&P 500 stock data is a tabular stock market dataset of daily stock price information (market, high price, low price, closing price, trading volume, etc.) for the last five years (the latest data is until February 2018) of all companies in the S&P 500 index.

2) Data Utilization (1) S&P 500 stock data has characteristics that: • Each row contains key stock metrics such as date, open, high, low, close, volume, and stock ticker name. • Data is provided as individual stock files and all stock integrated files, so it can be used for various analysis purposes. (2) S&P 500 stock data can be used to: • Stock Price Forecasting and Investment Strategy Development: Using historical stock price data, a variety of investment strategies and forecasting models can be developed, including time series forecasting, volatility analysis, and moving averages. • Market Trends and Corporate Comparison Analysis: It can be used to visualize stock price fluctuations across stocks, compare performance between stocks, analyze market trends, optimize portfolios, and more.

View monthly updates and historical trends for S&P 500 Market Cap. from United States. Source: Standard and Poor's. Track economic data with YCharts analy…

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, 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 December of 2025.

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.

Feb 2018 note: I have just updated the dataset to include data up to Feb 2018. I have also accounted for changes in the stocks on the S&P 500 index (RIP whole foods etc. etc.).

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).

The folder individual_stocks_5yr contains files of data for individual stocks, labelled by their stock ticker name. The all_stocks_5yr.csv contains the same data, presented in a merged .csv file. 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

Due to volatility in google finance, for the newest version I have switched over to acquiring the data from The Investor's Exchange api, the simple script I use to do this is found here. Special thanks to Kaggle, Github, pandas_datareader 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!

Index Time Series for Vanguard S&P 500 ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund employs an indexing investment approach designed to track the performance of the Standard & Poor's 500 Index, a widely recognized benchmark of U.S. stock market performance that is dominated by the stocks of large U.S. companies. The advisor attempts to replicate the target index by investing all, or substantially all, of its assets in the stocks that make up the index, holding each stock in approximately the same proportion as its weighting in the index. The fund is non-diversified.

Context

Historical data of S&P 500 Index

Content

This dataset includes the historical data of S&P 500 index from 1927 to 2020 with columns of date, opening price, highest price, lowest price, closing price, adjusted closing price, and the number of shares traded each day.

Acknowledgements

https://finance.yahoo.com/

Inspiration

Inspired from this dataset: https://www.kaggle.com/borismarjanovic/price-volume-data-for-all-us-stocks-etfs