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.

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.

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.

The main stock market index in the United States (US500) decreased 158 points or 2.69% since the beginning of 2025, 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 March of 2025.

Currency and split-adjusted pricing data across open, close, high, low, volume, adjustment factor, shares outstanding, volume-weighted average price and other data points.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Why Has the Stock Market Risen So Much Since the US Presidential Election?, PIIE Policy Brief 18-4. If you use the data, please cite as: Blanchard, Olivier, Christopher G. Collins, Mohammad R. Jahan-Parvar, Thomas Pellet, and Beth Anne Wilson. (2018). Why Has the Stock Market Risen So Much Since the US Presidential Election?. PIIE Policy Brief 18-4. Peterson Institute for International Economics.

NYSE American Integrated is a proprietary data feed that provides full order book depth, including every quote and order at each price level, on the American market (formerly AMEX, the American Stock Exchange). It operates on NYSE's Pillar platform and disseminates all order book activity in an order-by-order view of events, including trade executions, order modifications, cancellations, and other book updates.

NYSE American specializes in listing growing companies and is the leading exchange for small-cap stocks, as well as offering mid-cap insights. As of January 2025, it represented approximately 0.23% of the average daily volume (ADV) across all exchange-listed securities.

With L3 granularity, NYSE American Integrated captures information beyond the L1, top-of-book data available through SIP feeds, enabling accurate modeling of the book imbalances, trade directionality, quote lifetimes, and more. This data includes explicit trade aggressor side, odd lots, and auction imbalances. Auction imbalances offer valuable insights into NYSE American’s opening and closing auctions by providing details like imbalance quantity, paired quantity, imbalance reference price, and book clearing price.

Historical data is available for usage-based rates or with any Databento US Equities subscription. Visit our pricing page for more details or to upgrade your plan.

Asset class: Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

The main stock market index in Brazil (IBOVESPA) increased 12164 or 10.11% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Brazil. Brazil Stock Market (BOVESPA) - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index in Poland (WIG) increased 18251 points or 22.94% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Poland. Warsaw Stock Exchange WIG Index - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index in Italy (IT40) increased 4872 points or 14.25% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Italy. Italy Stock Market Index (IT40) - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index in Saudi Arabia (TASI) decreased 95 points or 0.79% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Saudi Arabia. Saudi Arabia Stock Market (TASI) - values, historical data, forecasts and news - updated on March of 2025.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-03-27 to 2025-03-26 about stock market, average, industry, and USA.

The main stock market index in Greece (Athens General) increased 276 points or 18.78% since the beginning of 2025, 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 March of 2025.

This dataset contains a detailed information on companies listed in the NYSE (The New York Stock Exchange).

The main stock market index in Laos (LSX Composite) decreased 43 points or 3.73% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Laos. Laos Securities Exchange Composite Index - values, historical data, forecasts and news - updated on March of 2025.

Japan JP: Market Capitalization: Listed Domestic Companies data was reported at 6,222.825 USD bn in 2017. This records an increase from the previous number of 4,955.300 USD bn for 2016. Japan JP: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 3,005.697 USD bn from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 6,222.825 USD bn in 2017 and a record low of 21.530 USD bn in 1977. Japan JP: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

France FR: Stocks Traded: Total Value: % of GDP data was reported at 40.973 % in 2014. This records an increase from the previous number of 39.327 % for 2013. France FR: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 13.969 % from Dec 1975 (Median) to 2014, with 40 observations. The data reached an all-time high of 108.977 % in 2007 and a record low of 0.850 % in 1977. France FR: Stocks Traded: Total Value: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

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.

Dow Jones Industrial Average Index Target Price Prediction

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

Costa Rica CR: Market Capitalization: Listed Domestic Companies data was reported at 2.232 USD bn in 2022. This records an increase from the previous number of 2.041 USD bn for 2021. Costa Rica CR: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 1.901 USD bn from Dec 1993 (Median) to 2022, with 25 observations. The data reached an all-time high of 3.011 USD bn in 2017 and a record low of 357.000 USD mn in 1993. Costa Rica CR: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

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.

Can stock prices be predicted? (Jakarta Stock Exchange Composite Index Stock Forecast)

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