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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.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
Non-professional investors often try to find an interesting stock among those in an index (such as the Standard and Poor's 500, Nasdaq, etc.). They need only one company, the best, and they don't want to fail (perform poorly). So, the metric to optimize is accuracy, described as:
Accuracy = True Positives / (True Positives + False Positives)
And the predictive model can be a binary classifier.
The data covers the price and volume of shares of 31 NASDAQ companies in the year 2022.
Every data set I found to predict a stock price (investing) aims to find the price for the next day, and only for that stock. But in practical terms, people like to find the best stocks to buy from an index and wait a few days hoping to get an increase in the price of this investment.
Rows are grouped by companies and their age (newest to oldest) on a common date. The first column is the company. The following are the age, market, date (separated by year, month, day, hour, minute), share volume, various traditional prices of that share (close, open, high...), some price and volume statistics and target. The target is mainly defined as 1 when the closing price increases by at least 5% in 5 days (open market days). The target is 0 in any other case.
Complex features and target were made by executing: https://www.kaggle.com/code/luisandresgarcia/202307
Many thanks to everyone who participates in scientific papers and Kaggle notebooks related to financial investment.
We offer three easy-to-understand packages to fit your business needs. Visit intrinio.com/pricing to compare packages.
Bronze
The Bronze package is ideal for developing your idea and prototyping your platform with high-quality EOD options prices sourced from OPRA.
When you’re ready for launch, it’s a seamless transition to our Silver package for delayed options prices, Greeks and implied volatility, and unusual options activity, plus delayed equity prices.
Exchange Fees & Requirements:
This package requires no paperwork or exchange fees.
Bronze Benefits:
Silver
The Silver package is ideal for clients that want delayed options data for their platform, or for startups in the development and testing phase. You’ll get 15-minute delayed options data, Greeks, implied volatility, and unusual options activity, plus the latest EOD options prices and delayed equity prices.
You can easily move up to the Gold package for real-time options and equity prices, additional access methods, and premium support options.
Exchange Fees & Requirements:
If you subscribe to the Silver package and will not display the data outside of your firm, you’ll need to fill out a simplified exchange agreement and send it back to us. There are no exchange fees and we can provide immediate access to the data.
If you subscribe to the Silver package and will display the data outside of your firm, we’ll work with your team to submit the correct paperwork to OPRA for approval. Once approved, OPRA will bill exchange fees directly to your firm – typically $600-$2000/month depending on your use case. These fees are the same no matter what data provider you use. Per-user reporting is not required, so there are no variable per user fees.
Silver Benefits:
Gold
The Gold package is ideal for funded companies that are in the growth or scaling stage, as well as institutions that are innovating within the fintech space. This full-service solution offers real-time options prices, Greeks and implied volatility, and unusual options activity, as well as the latest EOD options prices and real-time equity prices.
You’ll also have access to our wide range of modern access methods, third-party data via Intrinio’s API with licensing assistance, support from our team of expert engineers, custom delivery architectures, and much more.
Exchange Fees & Requirements:
If you subscribe to the Gold package, we’ll work with your team to submit the correct paperwork to OPRA for approval. Once approved, OPRA will bill exchange fees directly to your firm – typically $600-$2000/month depending on your use case. These fees are the same no matter what data provider you use. Per-user reporting is required, with an associated variable per user fee.
Gold Benefits:
Platinum
Don’t see a package that fits your needs? Our team can design a premium custom package for your business.
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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.
The UK House Price Index is a National Statistic.
Download the full UK House Price Index data below, or use our tool to https://landregistry.data.gov.uk/app/ukhpi?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=tool&utm_term=9.30_21_05_25" class="govuk-link">create your own bespoke reports.
Datasets are available as CSV files. Find out about republishing and making use of the data.
This file includes a derived back series for the new UK HPI. Under the UK HPI, data is available from 1995 for England and Wales, 2004 for Scotland and 2005 for Northern Ireland. A longer back series has been derived by using the historic path of the Office for National Statistics HPI to construct a series back to 1968.
Download the full UK HPI background file:
If you are interested in a specific attribute, we have separated them into these CSV files:
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price&utm_term=9.30_21_05_25" class="govuk-link">Average price (CSV, 7MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-Property-Type-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price_property_price&utm_term=9.30_21_05_25" class="govuk-link">Average price by property type (CSV, 15.3KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Sales-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=sales&utm_term=9.30_21_05_25" class="govuk-link">Sales (CSV, 5.2KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Cash-mortgage-sales-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=cash_mortgage-sales&utm_term=9.30_21_05_25" class="govuk-link">Cash mortgage sales (CSV, 4.9KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/First-Time-Buyer-Former-Owner-Occupied-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=FTNFOO&utm_term=9.30_21_05_25" class="govuk-link">First time buyer and former owner occupier (CSV, 4.5KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/New-and-Old-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=new_build&utm_term=9.30_21_05_25" class="govuk-link">New build and existing resold property (CSV, 11.0KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index&utm_term=9.30_21_05_25" class="govuk-link">Index (CSV, 5.5KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-seasonally-adjusted-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index_season_adjusted&utm_term=9.30_21_05_25" class="govuk-link">Index seasonally adjusted (CSV, 195KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-price-seasonally-adjusted-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average-price_season_adjusted&utm_term=9.30_21_05_25" class="govuk-link">Average price seasonally adjusted (CSV, 205KB)
<a rel="external" href="https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Repossession-2025-03.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=repossession&utm_term=9.30_21_05
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Graph and download economic data for Financial Market: Share Prices for Chile (SPASTT01CLM661N) from Jan 1990 to Jun 2025 about Chile and stock market.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Kenya's main stock market index, the Nairobi 20, rose to 2569 points on August 8, 2025, gaining 0.79% from the previous session. Over the past month, the index has climbed 0.50% and is up 58.11% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Kenya. Kenya Stock Market (NSE20) - values, historical data, forecasts and news - updated on August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Natural gas fell to 3 USD/MMBtu on August 8, 2025, down 2.33% from the previous day. Over the past month, Natural gas's price has fallen 6.80%, but it is still 39.78% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on August of 2025.
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Graph and download economic data for Financial Market: Share Prices for United Kingdom (SPASTT01GBQ661N) from Q1 1958 to Q2 2025 about stock market and United Kingdom.
Datasets are available as CSV files. Find out about republishing and making use of the data.
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/UK-HPI-full-file-2016-09.csv" class="govuk-link">UK HPI full file (CSV, 42.5MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-2016-09.csv" class="govuk-link">Average price.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-Property-Type-2016-09.csv" class="govuk-link">Average price by property type.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Sales-2016-09.csv" class="govuk-link">Sales.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Cash-mortgage-sales-2016-09.csv" class="govuk-link">Cash mortgage sales.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/First-Time-Buyer-Former-Owner-Occupied-2016-09.csv" class="govuk-link">First time buyer and former owner occupied.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/New-and-Old-2016-09.csv" class="govuk-link">New build and existing resold property.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-2016-09.csv" class="govuk-link">Index.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-seasonally-adjusted-2016-09.csv" class="govuk-link">Index seasonally adjusted.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-price-seasonally-adjusted-2016-09.csv" class="govuk-link">Average Price seasonally adjusted.csv
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Repossession-2016-09.csv" class="govuk-link">Repossessions.csv
This file includes a derived back series for the new UK HPI. Under the UK HPI, data is available from 1995 for England and Wales, 2004 for Scotland and 2005 for Northern Ireland. A longer back series has been derived by using the historic path of the ONS HPI to construct a series back to 1968:
The release calendar shows when the next month’s data will be published.
Create your own reports based on the UK House Price Index data, http://landregistry.data.gov.uk/app/ukhpi" class="govuk-link">use our tool.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Nigeria's main stock market index, the NSE-All Share, fell to 145757 points on August 8, 2025, losing 0.56% from the previous session. Over the past month, the index has climbed 19.48% and is up 47.82% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Nigeria. Nigeria Stock Market NSE - values, historical data, forecasts and news - updated on August of 2025.
https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer
With LSEG's Tokyo Stock Exchange (TSE) Data, gain full access to benchmarks, indices, reference data, market depth data, and more.
https://academictorrents.com/nolicensespecifiedhttps://academictorrents.com/nolicensespecified
Data collected and formatted by Justin Timperio: "In my exploration of world of big data and I became curious about tick data. Tick data is extremely granular and provides a great challenge for those looking to work on their optimization skills due to its size. Unfortunately, market data is almost always behind a pay wall or de-sampled to the point of uselessness. After discovering the Dukascopy api, I knew I wanted to make this data available for all in a more accessible format." Total Line Count: 8,495,770,706 Total Data Points: 33,983,082,824 Total Decompressed Size: 501 GB
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.
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Graph and download economic data for Stock Market Total Value Traded to GDP for Chile (DDDM02CLA156NWDB) from 1980 to 2020 about Chile, market cap, stock market, trade, and GDP.
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Graph and download economic data for Money Market Funds; Total Financial Assets, Level (MMMFFAQ027S) from Q4 1945 to Q1 2025 about MMMF, IMA, financial, assets, and USA.
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Graph and download economic data for Index of Spot Market Prices of 13 Raw Industrial Commodities for United States (M0401BUSM350NNBR) from Jul 1946 to Jun 1968 about commodities, industry, price index, indexes, price, and USA.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
This dataset displays the name, website and locations of Ontario Farmers Markets, as derived from the Farmers Markets of Ontario Website.
The 2 datasets available below are zipped files containing:
For instructions on how to use Google Earth, read the Google Earth tutorial.
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Graph and download economic data for Financial Market: Share Prices for Sweden (SPASTT01SEM661N) from Jan 1950 to Jun 2025 about Sweden and stock market.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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.