From the first quarter of 2019 to the last quarter of 2021, the most lucrative sector in terms of IPO proceeds on the NASDAQ was financials. The value of IPOs in this sector amounted to approximately *** billion U.S. dollars during the period considered.

The main stock market index of United States, the US500, fell to 6450 points on August 15, 2025, losing 0.29% from the previous session. Over the past month, the index has climbed 2.97% and is up 16.12% compared to the same time last year, 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 August of 2025.

Context

The algorithmic trading space is buzzing with new strategies. Companies have spent billions in infrastructures and R&D to be able to jump ahead of the competition and beat the market. Still, it is well acknowledged that the buy & hold strategy is able to outperform many of the algorithmic strategies, especially in the long-run. However, finding value in stocks is an art that very few mastered, can a computer do that?

Content

This Data repo contains two datasets:

1. Example_2019_price_var.csv. I built this dataset thanks to Financial Modeling Prep API and to pandas_datareader. Each row is a stock from the technology sector of the US stock market (that is available from the aforementioned API, which is free and highly recommended). The column contains the percent price variation of each stock for the year 2019. In other words, it collects the percent price variation of each stock from the first trading day on Jan 2019 to the last trading day of Dec 2019. To compute this price variation I decided to consider the Adjusted Close Price.

2. Example_DATASET.csv. I built this dataset thanks to Financial Modeling Prep API. Each row is a stock from the technology sector of the US stock market (that is available from the aforementioned API). Each column is a financial indicator that can be found in the 2018 10-K filings of each company. There are no Nans or empty cells. Furthermore, the last column is the CLASS of each stock, where:

   1. class = 1 if the price of the stock increases during 2019
   2. class = 0 if the price of the stock decreases during 2019

In other words, the last column is used to classify each stock in buy-worthy or not, and this relationship is what should allow a machine learning model to learn to recognize stocks that will increase their value from those that won't.

NOTE: the number of stocks does not match between the two datasets because the API did not have all the required financial indicators for some stocks. It is possible to remove from Example_2019_price_var.csv those rows that do not appear in Example_DATASET.csv.

Inspiration

I built this dataset during the 2019 winter holidays period, because I wanted to answer a simple question: is it possible to have a machine learning model learn the differences between stocks that perform well and those that don't, and then leverage this knowledge in order to predict which stock will be worth buying? Moreover, is it possible to achieve this simply by looking at financial indicators found in the 10-K filings?

From 2010 to 2019, the number of initial public offerings (IPOs) on the Nasdaq Stock Exchange fluctuated. After that period, sharp increases were recorded for the number of deals. The largest jump in number of IPOs was in 2021 when deal volume peaked at ***. In the following years, however, the number of IPOs decreased and amounted to *** in 2024.

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 Settle - NASDAQ-100 Mini (NASDAQXMS1) from 2019-03-01 to 2025-08-12 about NASDAQ, indexes, and USA.

In 2025, most of the Polish population stated they know very little about the stock market. Only *** percent had a lot of knowledge, while *** percent had rather little knowledge.

The 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 – 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.

Between 2000 and 2024, the value of the Nasdaq Industrial Index increased nearly tenfold. As of December 29, 2023, the value of this index reached *********, up from ******* in the previous year. The largest increase was recorded between 2019 and 2020.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-08-17 to 2025-08-14 about stock market, average, industry, and USA.

United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Diversified REITs Index data was reported at 1,608.960 NA in Apr 2025. This records a decrease from the previous number of 1,661.450 NA for Mar 2025. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Diversified REITs Index data is updated monthly, averaging 1,488.120 NA from Dec 2012 (Median) to Apr 2025, with 149 observations. The data reached an all-time high of 1,982.860 NA in Oct 2019 and a record low of 1,084.410 NA in Dec 2012. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Diversified REITs Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: NASDAQ: Net Total Return: Monthly.

benstaf/FNSPID-nasdaq-100-post2019-1newsperrow dataset hosted on Hugging Face and contributed by the HF Datasets community

Graph and download economic data for Nasdaq Latin America Energy Large Mid Cap NTR Index (NASDAQNQLA60LMN) from 2019-03-18 to 2025-08-04 about mid cap, NASDAQ, Latin America, market cap, large, energy, and indexes.

United Kingdom's main stock market index, the GB100, rose to 9177 points on August 14, 2025, gaining 0.13% from the previous session. Over the past month, the index has climbed 2.67% and is up 9.94% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on August of 2025.

PURPOSE (possible uses)

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.

Context

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.

Content

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

Thanks

Many thanks to everyone who participates in scientific papers and Kaggle notebooks related to financial investment.

United States NASDAQ: Index: NASDAQ US Benchmark Diversified REITs Index data was reported at 948.520 NA in Apr 2025. This records a decrease from the previous number of 980.090 NA for Mar 2025. United States NASDAQ: Index: NASDAQ US Benchmark Diversified REITs Index data is updated monthly, averaging 1,071.640 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,421.980 NA in Oct 2019 and a record low of 799.150 NA in Mar 2020. United States NASDAQ: Index: NASDAQ US Benchmark Diversified REITs Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: NASDAQ: Monthly.

This dataset contains MACD, EMA, SMA, ADX, CMO, RSI, BBANDS, and ATR metrics for Nasdaq100 and Dow stocks for the timeperiod between Jan-2019 and May-2025

IPOs in the healthcare sector raised the most proceeds on the Nasdaq Helsinki during the period from the first quarter of 2019 to the last quarter of 2021. IPO proceeds in this sector amounted to approximately *** billion U.S. dollars. This was followed by the consumer discretionary sector, with approximately *** million U.S. dollars in IPO proceeds.

Graph and download economic data for Nasdaq Brazil Energy Large Mid Cap NTR Index (NASDAQNQBR60LMN) from 2019-03-18 to 2025-08-08 about mid cap, NASDAQ, market cap, Brazil, large, energy, and indexes.

Download Micro E-Mini Nasdaq-100 Futures (CME) (HWB1 Index) historical futures data — 1m, 5m, 10m, 30m, 1h, Daily — from 2019-May-06 to 2025-Jul-16