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.

The "Stock Market Dataset for AI-Driven Prediction and Trading Strategy Optimization" is designed to simulate real-world stock market data for training and evaluating machine learning models. This dataset includes a combination of technical indicators, market metrics, sentiment scores, and macroeconomic factors, providing a comprehensive foundation for developing and testing AI models for stock price prediction and trading strategy optimization.

Key Features Market Metrics:

Open, High, Low, Close Prices: Daily stock price movement. Volume: Represents the trading activity during the day. Technical Indicators:

RSI (Relative Strength Index): A momentum oscillator to measure the speed and change of price movements. MACD (Moving Average Convergence Divergence): An indicator to reveal changes in strength, direction, momentum, and duration of a trend. Bollinger Bands: Upper and lower bands around a stock price to measure volatility. Sentiment Analysis:

Sentiment Score: Simulated sentiment derived from financial news and social media, ranging from -1 (negative) to 1 (positive). Macroeconomic Factors:

GDP Growth: Indicates the overall health and growth of the economy. Inflation Rate: Reflects changes in purchasing power and economic stability. Target Variable:

Buy/Sell Signal: Binary classification (1 = Buy, 0 = Sell) based on price movement thresholds, simulating actionable trading decisions. Use Cases AI Model Training: Ideal for building stock prediction models using LSTM, Gradient Boosting, Random Forest, etc. Trading Strategy Optimization: Enables testing of trading algorithms and strategies in a simulated environment. Sentiment Analysis Research: Useful for understanding how sentiment influences stock movements. Feature Engineering and Selection: Provides a diverse set of features for experimentation with advanced techniques like PCA and LDA. Dataset Highlights Synthetic Yet Realistic: Carefully designed to mimic real-world financial data trends and relationships. Comprehensive Coverage: Includes key indicators and metrics used by traders and analysts. Scalable: Suitable for use in both small-scale academic projects and larger AI-driven trading platforms. Accessible for All Levels: The intuitive structure ensures that even beginners can utilize this dataset for financial machine learning applications. File Format The dataset is provided in CSV format, where:

Rows represent individual trading days. Columns represent features (technical indicators, market metrics, etc.) and the target variable. Acknowledgments This dataset is synthetically generated and is intended for research and educational purposes. It is not based on real market data and should not be used for actual trading.

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.

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.

Many academics and analysts have found it challenging to master the art of predicting stock values. Investors are actually quite interested in the field of stock price forecasting research. Many investors are interested in knowing the stock market's future scenario in order to make a smart and successful investment. By giving helpful information like the stock market's future direction, good and successful stock market prediction systems assist traders, investors, and analysts.

This dataset contains the stock prices of Google since the COVID-19 pandemic began. There are 7 columns in this dataset:

📉 GOOGL Daily Stock Prices (2004–2025)

📌 Overview

This dataset offers complete historical daily stock prices for Alphabet Inc. (GOOGL). Spanning from GOOGL’s IPO in 2004 through to the present, it provides a clean and consistent view of stock performance over time.

Whether you’re building predictive models, testing trading strategies, or visualizing long-term price movements, this dataset is ready to use with just a few lines of code.

🔗 Use Together With My Other GOOGL Datasets!

This dataset is part of a larger ecosystem of Google/Alphabet-related datasets I created. You can use them together for powerful, multi-dimensional analysis:

👉 GOOGL Financial Dataset: Quarterly Reports + Daily Prices
Includes quarterly income statements, balance sheets, cash flow statements, and another source of daily prices for cross-verification or model ensembling.

👉 GOOGL Daily News — 2000 to 2025
Provides daily news headlines and summaries related to Alphabet Inc., perfect for sentiment analysis, event-based forecasting, and correlating news with stock prices.

Combine all three datasets to:

• Analyze how news sentiment affects stock performance
• Correlate earnings announcements with market reaction
• Build predictive models that integrate both fundamentals and external signals

📁 Columns

1. open – Opening stock price of the day
2. high – Highest price reached that day
3. low – Lowest price during the day
4. close – Closing price of the trading day
5. volume – Volume of shares traded
date (index) – Trading date

1) Data Introduction • The Twitter Stock Prices Dataset contains stock price data for Twitter from November 2013 to October 2022. This dataset is a time series dataset that provides daily stock trading information. • The key attributes include the stock's opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and volume (Volume).

2) Data Utilization (1) Characteristics of the Twitter Stock Prices Data • This dataset is a time series, offering daily stock price fluctuations and allows tracking of price changes over time. • It includes 7 main attributes related to stock trading, allowing for analysis of price movements (open, high, low, close) and volume, to better understand Twitter’s stock price dynamics. • This data helps analyze market trends, price volatility patterns, and price fluctuation analysis, providing insights into the dynamics of the stock market.

(2) Applications of the Twitter Stock Prices Data • Predictive Modeling: This dataset can be used to develop stock price prediction models, including predicting price increases/decreases or forecasting future stock prices using machine learning models. • Business Insights: Investment experts can use this dataset to evaluate Twitter’s stock performance, and it provides useful information for optimizing investment strategies in response to market changes. This dataset can be used for trend forecasting and investor analysis. • Trend Analysis: By analyzing stock upward/downward trends, this dataset can help evaluate the company's market performance and develop trend-based investment strategies.

Graph and download economic data for American Railroad Stock Prices for United States (M11005USM293NNBR) from Jan 1855 to Jan 1937 about railroad, stock market, and USA.

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.

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.

Graph and download economic data for Financial Market: Share Prices for France (SPASTT01FRM661N) from Jan 1955 to Oct 2025 about France and stock market.

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.

DIA stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Context

Take a look at historical stock prices of major social media companies.

Content

Meta (Facebook), Twitter, Snap, Pinterest and Etsy historical stock prices.

Reckitt Benckiser stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Sapporo stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

TJX Companies stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.