The main stock market index of United States, the US500, rose to 6464 points on September 1, 2025, gaining 0.06% from the previous session. Over the past month, the index has climbed 2.13% and is up 16.92% 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 September of 2025.

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.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-08-31 to 2025-08-29 about stock market, average, industry, and USA.

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?

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.

Dataset Description

Overview:

This dataset contains the historical stock prices and related financial information for five major technology companies: Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Google (GOOGL), and Tesla (TSLA). The dataset spans a five-year period from January 1, 2019, to January 1, 2024. It includes key stock metrics such as Open, High, Low, Close, Adjusted Close, and Volume for each trading day.

Data Collection:

The data was sourced using the yfinance library in Python, which provides convenient access to historical market data from Yahoo Finance.

Contents:

The dataset contains the following columns:

Date: The trading date. Open: The opening price of the stock on that date. High: The highest price of the stock on that date. Low: The lowest price of the stock on that date. Close: The closing price of the stock on that date. Adj Close: The adjusted closing price, accounting for dividends and splits. Volume: The number of shares traded on that date. Ticker: The stock ticker symbol representing each company.

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.

This statistic shows the influence of the flat tax on people's interest in investing in the stock market in France in February 2019. At that time, the flat tax didn't have much influence on French people's interest in investing in the stock market as ** percent of people didn't know what the flat tax was. Among people who knew what the flat tax was, ** percent claimed that it did not influence their interest at all.

United Kingdom's main stock market index, the GB100, fell to 9117 points on September 2, 2025, losing 0.87% from the previous session. Over the past month, the index has declined 0.13%, though it remains 9.86% higher than a year ago, 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 September of 2025.

On January 29, 2024 the AEX index closed at ****** points - significantly higher than the 2020 low of ***** points recorded on March 18, 2020. The AEX Index, the index of the ** biggest stocks on the Amsterdam Stock Exchange, saw heavy losses early March 2020 due to economic uncertainties following the coronavirus pandemic. On top, there was an unexpected decrease in oil prices, as announced by Saudi Arabia over a dispute with Russia. This caused stocks like Royal Dutch Shell, the Netherlands' biggest listed company, to go down significantly.

As of January 29, 2025, the FTSE index stood at ******** points - well above its average value of around ***** points in the past few years.On the 12th of March 2020, amid the escalating crisis surrounding the coronavirus and fears of a global recession, the FTSE 100 suffered the second largest one day crash in its history and the biggest since the 1987 market crash. On the 23rd of March, the FTSE index saw its lowest value this year to date at ******** but has since began a tentative recovery. With the continuation of the pandemic, the FTSE 100 index was making a tentative recovery between late March 2020 and early June 2020. Since then the FSTE 100 index had plateaued towards the end of July, before starting a tentative upward trend in November. FTSE 100 The Financial Times Stock Exchange 100 Index, otherwise known as the FTSE 100 Index is a share index of the 100 largest companies trading on the London Stock Exchange in terms of market capitalization. At the end of March 2024, the largest company trading on the LSE was Shell. The largest ever initial public offering (IPO) on the LSE was Glencore International plc. European stock exchanges While nearly every country in Europe has a stock exchange, only five are considered major, and have a market capital of over one trillion U.S dollars. European stock exchanges make up two of the top ten major stock markets in the world. Europe’s biggest stock exchange is the Euronext which combines seven markets based in Belgium, France, England, Ireland, the Netherlands, Norway, and Portugal.

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.

India's main stock market index, the SENSEX, rose to 80364 points on September 1, 2025, gaining 0.70% from the previous session. Over the past month, the index has declined 0.81% and is down 2.66% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on September of 2025.

Stock Market Value to GDP - Historical chart and current data through 2019.

Botswana: Stock market value traded w/o top 10 firms, % of total value traded: Pour cet indicateur, The World Federation of Exchanges fournit des données pour la Botswana de 2019 à 2019. La valeur moyenne pour Botswana pendant cette période était de 48.1 pour cent avec un minimum de 48.1 pour cent en 2019 et un maximum de 48.1 pour cent en 2019.

Graph and download economic data for Stock Market Total Value Traded to GDP for Norway (DDDM02NOA156NWDB) from 1980 to 2019 about market cap, Norway, stock market, trade, and GDP.

Graph and download economic data for Stock Market Total Value Traded to GDP for Croatia (DDDM02HRA156NWDB) from 1995 to 2019 about Croatia, market cap, stock market, trade, and GDP.

Indonesia's main stock market index, the JCI, fell to 7710 points on September 1, 2025, losing 1.54% from the previous session. Over the past month, the index has climbed 3.29% and is up 0.20% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Indonesia. Indonesia Stock Market (JCI) - values, historical data, forecasts and news - updated on September of 2025.

• Rolling Stock Market Scope:

The report on Rolling Stock Market offers in-depth analysis on market trends, drivers, restraints, opportunities etc. Along with qualitative information, this report include the quantitative analysis of various segments in terms of market share, growth, opportunity analysis, market value, etc. for the forecast years. The global rolling stock market is segmented on the basis of type, application and geography.

The worldwide market for Rolling Stock Market is expected to grow at a CAGR of roughly x.x% over the next ten years and will reach US$ XX.X Mn in 2028, from US$ XX.X Mn in 2018, according to a new Market.us (Prudour Research) study. Read More

Stock Market Total Value Traded to GDP for United States was 108.51% in January of 2019, according to the United States Federal Reserve. Historically, Stock Market Total Value Traded to GDP for United States reached a record high of 319.88 in January of 2008 and a record low of 7.97 in January of 1977. Trading Economics provides the current actual value, an historical data chart and related indicators for Stock Market Total Value Traded to GDP for United States - last updated from the United States Federal Reserve on September of 2025.