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.

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.

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.

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.

This dataset contains 20+ years of all items in the American art category sold on auction by Christie’s, Sotheby’s, Bonhams and Phillips from 2000 to date.

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.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities of sales by type of processor on a monthly basis.

Introduction: The "Cryptocurrency Price Analysis Dataset: BTC, ETH, XRP, LTC (2018-2023)" is a comprehensive dataset that captures the daily price movements of six popular cryptocurrencies. It covers a period from January 1, 2018, to May 31, 2023, providing a valuable resource for researchers, analysts, and enthusiasts interested in studying the historical price behavior of these digital assets.

Description: This dataset contains a wealth of information for six major cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC). The data spans a time frame of over five years, enabling users to explore long-term trends, analyze volatility patterns, and gain insights into market dynamics.

Columns:

1. Crypto: This column specifies the name of the cryptocurrency (e.g., BTC, ETH, XRP, LTC).
2. Date: The date on which the price data was recorded.
3. Open: The opening price of the cryptocurrency at the beginning of the day.
4. High: The highest price reached by the cryptocurrency during the day.
5. Low: The lowest price reached by the cryptocurrency during the day.
6. Close: The closing price of the cryptocurrency at the end of the day.

Use Cases: The dataset offers numerous possibilities for analysis and research within the field of cryptocurrencies. Here are a few potential use cases:

1. Price Analysis: Researchers can investigate the historical price movements of each cryptocurrency to identify trends, patterns, and potential correlations between different assets.
2. Volatility Study: The dataset enables the study of volatility in cryptocurrency markets, helping users understand the frequency and magnitude of price fluctuations.
3. Market Performance: Analysts can analyze the performance of individual cryptocurrencies over time, comparing returns and risk measures to assess their investment potential.
4. Trading Strategies: Traders can utilize the dataset to develop and backtest trading strategies based on technical indicators, price patterns, or machine learning algorithms.
5. Sentiment Analysis: Combine this dataset with external sentiment data to explore the relationship between market sentiment and cryptocurrency price movements. By sharing this dataset on Kaggle, you are providing a valuable resource to the data science community, encouraging collaborative research, and enabling the development of innovative models and solutions within the cryptocurrency domain.

Please note that this dataset is for educational and research purposes only and should not be used for making financial decisions without thorough analysis and consultation with financial professionals.

View daily updates and historical trends for Bitcoin Market Cap. Source: Blockchain.com. Track economic data with YCharts analytics.

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.

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of ETH-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Description:

Empowering Indian Investors: NSE's Historical Yearly Financial Ratios for 1800 Stocks with Predictive Modeling and Strategy Backtesting

Financial data is the lifeblood of investment analysis and decision-making, and for Indian investors navigating the dynamic National Stock Exchange (NSE), access to comprehensive and tailored datasets is crucial. The NSE 1800 Stocks Historical Yearly Financial Ratios dataset is a valuable resource designed to empower Indian investors, analysts, and financial professionals with the essential financial information needed for predictive modeling and strategy backtesting within the context of the Indian stock market.

Motivation:

The Indian stock market presents unique opportunities and challenges. The motivation behind this dataset is to provide Indian investors with a robust financial dataset that enables them to perform predictive modeling and strategy backtesting independently. It aims to streamline the analysis process, promote data-driven decision-making, and enhance the understanding of Indian stock market dynamics.

Context:

Understanding the financial performance of Indian companies is fundamental for Indian investors, and this dataset offers a wealth of historical financial metrics and ratios for 1800 stocks listed on the NSE. It is distinguished by the ability to:

1 Perform Predictive Modeling: Users can leverage this dataset to build their predictive models tailored to the Indian market's unique characteristics. These models can assist investors in forecasting financial metrics, stock prices, and market trends specific to the Indian context.

2 Conduct Strategy Backtesting: Indian investors can independently test their investment strategies using historical data from the NSE. This dataset serves as the foundation for users to assess the performance of their strategies while considering factors such as Indian economic cycles, regulatory changes, and market dynamics.

3 Evaluate Financial Health: Users can assess the financial stability, profitability, and operational efficiency of Indian companies by utilizing a comprehensive collection of historical financial ratios and metrics.

4 Support Informed Decision-Making: By providing access to the historical financial data of 1800 stocks listed on the NSE, this dataset equips Indian investors with the information needed to make well-informed investment decisions, navigate the Indian stock market, and manage their portfolios effectively.

In summary, the NSE 1800 Stocks Historical Yearly Financial Ratios for Predictive Modeling and Strategy Backtesting (Tailored for Indian Investors) dataset is a robust resource that empowers Indian investors to independently perform predictive modeling and strategy backtesting. It serves as a foundational dataset to support data-driven investment decisions within the unique context of the Indian stock market. Whether you are an Indian investor, analyst, or financial professional, this dataset equips you with the financial data needed to enhance your investment strategies and decision-making.

Israel's main stock market index, the TA-125, rose to 3538 points on December 2, 2025, gaining 1.75% from the previous session. Over the past month, the index has climbed 4.40% and is up 50.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on December of 2025.

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

China Stock Market - Shanghai Composite Index - Historical chart and current data through 2025.

A collection of financial datasets that are regularly updated

Day Level Data | Type | Link | | --- | --- | | Stocks | https://www.kaggle.com/datasets/liewyousheng/historical-stock-dataset | | ETF | https://www.kaggle.com/datasets/liewyousheng/historical-etf |

Blockchain data query: Perennial - Historical Market orderCreated Event Data Decoded (v2.1 and prior)

This dataset organized stock market data from 01-04-2023 to 05-13-2024 from Yahoo Finance. The dataset is intended to perform machine learning tasks include but not limited to: 1. Simple Linear Regression 2. Multiple Linear Regression 3. Multivariate Regression Test ( implemented in this project and analyzed in the report) 4. PCA ( implemented in this project and analyzed in the report) 5. Factor Analysis ( implemented in this project and analyzed in the report) 6. ARIMA

The key idea is to utilize historical stock market dataset to predict Next Day adjusted close price by using various variables. The predictive power and importance of each variable will be evaluated using PCA and VIF score.

The project aims to figure out the feasibility to predict stock market adjusted closing price for the trendy AI stock NVIDIA and filter out the most important indicator of stock price prediction.

Features included in this dataset:

• Predictive Variable: Next Day Adjusted Close price
• Independent Variables and its Types

1. Date ( Time Series, Numerical) 2.Prior DayOpen ( Numerical)
2. LogRange ( Stock Daily High - Low, risk indicator) ***Risk Indicator
3. Log_Volume (Log Value of Daily Traded Volume) ***Momentum Indicator
4. Return_Percentage ( [Today AdjClose - Prior Day AdjClose)/Prior Day AdjClose]*100% ) ***This is a profit Indicator
5. 3_Day_Avg_AdjClose(Market Price Level Assassin indicatory, Delay=3) *** Historical Market Price Level Assessment
6. PriorDay_AdjClose ( prior day adjusted closed price)

The market capitalization of stablecoin Tether in November 2021 was roughly ************* U.S. dollars higher than it was *** month before. In 2021, Tether ranks as *** of the biggest cryptocurrencies in the world and is regarded as the most well-known "stablecoin", or cryptocurrency that is connected to the price development of another, real-world asset. This particular segment made up roughly half of the overall value locked in Decentralized Finance or DeFi.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Multiple and All Other Food Uses" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".