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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.
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TwitterThis dataset offers comprehensive historical stock market data covering over 9,000 tickers from 1962 to the present day. It includes essential daily trading information, making it suitable for various financial analyses, trend studies, and algorithmic trading model development.
This dataset is ideal for: - Time-Series Analysis: Track stock price trends over time, examining daily, monthly, and yearly patterns across sectors. - Algorithmic Trading: Develop and backtest trading strategies using historical price movements and volume data. - Machine Learning Applications: Train models for stock price prediction, volatility forecasting, or portfolio optimization. - Quantitative Research: Perform event studies, analyze the impact of dividends and stock splits, and assess long-term investment strategies. - Comparative Analysis: Evaluate performance across industries or against broader market trends by analyzing multiple tickers in one dataset.
This dataset serves as a robust resource for academic research, quantitative finance studies, and financial technology development.
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Greece's main stock market index, the Athens General, rose to 2108 points on December 2, 2025, gaining 0.41% from the previous session. Over the past month, the index has climbed 4.15% and is up 47.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Greece. Greece Stock Market (ASE) - values, historical data, forecasts and news - updated on December of 2025.
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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.
The date for every symbol is saved in CSV format with common fields:
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.
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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 provides a comprehensive, pre-processed collection of U.S. stock market data, specifically curated for quantitative analysis, financial modeling, and machine learning applications focused on volatility and asset pricing. It is optimized to include essential price and volume change metrics, along with market fundamentals, to facilitate efficient research.
The data is collected into previous 1000 & 3500 market open days since 10/12/2025. Note for a stock to be in each dataset it must have at least 1000 & 3500 days of history. The source data is located at https://stooq.com/db/h/ and an extract script can be found in my accompanying notebook.
The time-series data files (log_change.pkl) are optimized for quantitative modeling, where raw prices are replaced by daily change metrics to capture volatility and momentum efficiently.
The 3D array (trimmed_market_data_log_change_1000.pkl) is structured as (Days, Features, Tickers) and contains the following 5 features per day:
ticker
date
log_Ret (Close-to-Close): Logarithmic return, ln(Closetโ/Closetโ1โ). Used for overall volatility and total return.
log_Vol: Log change in volume, ln(Voltโ/Voltโ1โ). Used to measure trading activity change.
OC_Log_Change (Open-to-Close): Intraday logarithmic return, ln(Closetโ/Opentโ). Used to isolate intraday volatility from overnight gaps.
HL_Range_Pct: Daily High-Low range normalized by previous close, (HightโโLowtโ)/Closetโ1โ. Used as a proxy for realized daily volatility (Parkinson-like measure).
This file contains point in time cross-sectional data, including fields like:
Ticker
Company Name (e.g., Agilent Technologies, Inc.)
marketCap
sector
industry
Read using pd.read_pickle('')
Volatility Forecasting: Use the historical time-series features (Log_Ret, HL_Range_Pct) to train models (e.g., GARCH, machine learning) to predict future volatility.
Alpha Generation: Develop trading signals based on the cross-sectional fundamentals combined with recent momentum/volatility changes.
Anomaly Detection: Use the difference between overnight return (implied by CC minus OC) to detect potential mispricings or significant after-hours news impact.
Factor Modeling: Construct stock factors based on market capitalization, price levels, and the novel volatility features provided.
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Indonesia's main stock market index, the JCI, rose to 8617 points on December 2, 2025, gaining 0.80% from the previous session. Over the past month, the index has climbed 4.13% and is up 19.75% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Indonesia. Indonesia Stock Market (JCI) - values, historical data, forecasts and news - updated on December of 2025.
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TwitterThe 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 โ 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.
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France's main stock market index, the FR40, rose to 8121 points on December 2, 2025, gaining 0.29% from the previous session. Over the past month, the index has climbed 0.13% and is up 11.93% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on December of 2025.
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Argentina's main stock market index, the Merval, rose to 3060289 points on December 1, 2025, gaining 1.12% from the previous session. Over the past month, the index has declined 1.42%, though it remains 33.32% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Argentina. Argentina Stock Market (MERVAL) - values, historical data, forecasts and news - updated on December of 2025.
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This comprehensive dataset provides historical stock price data spanning various time periods, offering insights into the fluctuations and trends in the stock market over time. With records covering multiple decades, investors, analysts, and researchers can explore the dynamics of different stocks, industries, and market sectors.
The dataset includes essential information such as opening price, closing price, highest and lowest prices, trading volume, and adjusted closing prices. It encompasses a diverse range of stocks, including those from various exchanges and sectors, allowing for extensive analysis and comparison.
Researchers can utilize this dataset to conduct thorough analyses, develop financial models, backtest trading strategies, and gain a deeper understanding of market behavior. Investors can assess the performance of individual stocks or portfolios over extended periods, aiding in informed decision-making and risk management.
Whether you're a seasoned investor seeking historical insights or an analyst exploring market trends, this dataset serves as a valuable resource for studying the complexities of the stock market across different eras.
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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.
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Spain's main stock market index, the ES35, rose to 16493 points on December 2, 2025, gaining 0.63% from the previous session. Over the past month, the index has climbed 2.84% and is up 38.90% compared to the same time last year, 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 December of 2025.
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The dataset includes:
Stock Tickers: A comprehensive list of available stock tickers in Saudi Arabia, each identified with a .SR suffix. Historical Data: Time series data for each stock, including: Date: The trading date. Open: The opening price of the stock on that date. High: The highest price reached during the trading session. Low: The lowest price reached during the trading session. Close: The closing price of the stock on that date. Volume: The number of shares traded on that date. Ticker: The stock ticker symbol. The data spans from January 1, 2020, to January 1, 2024, providing a detailed view of stock performance over this period.
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TwitterIn 2025, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the financial crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.
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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
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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.
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This dataset provides historical stock prices of eBay Inc. (EBAY) from 1998 to the 2025. It includes key stock market data such as Open, High, Low, Close, Adjusted Close, and Volume, making it useful for financial analysis, stock market research, and predictive modeling.
๐น Ticker Symbol: EBAY
๐น Date Range: 1998 - Present
๐น Dataset Type: Time Series Data
| Column Name | Description |
|---|---|
| ๐ Date | Trading date (Index) |
| ๐ Open | Stock price at market open |
| ๐ High | Highest price during the trading day |
| ๐ Low | Lowest price during the trading day |
| ๐ฅ Close | Price at market close |
| โ Adj Close | Adjusted closing price after dividends/splits |
| ๐ Volume | Number of shares traded on that day |
โ
Stock Market Analysis โ Identify trends in eBayโs stock price
โ
Machine Learning & AI โ Train models for stock price prediction
โ
Financial Research โ Study historical patterns and volatility
โ
Time Series Forecasting โ Analyze long-term trends and patterns
This dataset has been extracted from Yahoo Finance and processed to remove unnecessary columns while retaining core stock market data.
Explore and analyze eBayโs stock history! ๐๐
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TwitterSince Investing.com does not have an API, I decided to develop this Python package in order to retrieve historical data from the companies that integrate the Continuous Spanish Stock Market. So on, I decided to generate, via investpy, the datasets for every company so that any Data Scientist or Data Enthusiastic can handle it and abstract their own conclusions and research.
The main purpose of developing investpy, the package from which these datasets have been retrieved, was to use it as the Data Extraction tool for its namesake section, for my Final Degree Project at the University of Salamanca titled "*Machine Learning for stock investment recommendation systems*". The package end up being so consistent, reliable and usable that it is going to be used as the main Data Extraction tool by another students in their Final Degree Projects named "*Recommender system of banking products*" and "*Robo-Advisor Application*".
investpy, the Python package from which datasets were generated is currently in a development beta version, so please, if needed open an issue to solve all the possible problems the package may be causing or any dataset error. Also, any new ideas or proposals are welcome, and will be gladly implemented in the package if the are positive and useful.
For further information or any question feel free to contact me via email at alvarob96@usal.es
You can also check my Medium Publication, where I upload weekly posts related to Data Science and mainly on Data Extraction techniques via Web Scraping. In this case, you can read "investpyโโโa Python package for historical data extraction from the Spanish stock market" where I explain the basics on investpy development and some insights on Web Scraping with Python.
This Python Package has been made for research purposes in order to fit a needs that Investing.com does not cover, so this package works like an Application Programming Interface (API) of Investing.com developed in an altruistic way. Conclude that this package is not related in any way with Investing.com or any dependant company, the only requirement for developing this package was to mention the source where data is retrieved.
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1.open: Price at opening time
2.Close: Price at closing time
3.High: Highest value of that stock on that day
4.Low: Lowest value of that stock on that day
5.Adj Close : It helps in getting an idea of the fair value of a stock
6.Volume - measure of the number of stocks traded over a specified period.
7.Date - Each Date contains the stock of that company at that date .
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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.