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.

The Dow Jones Composite Index finished the year 2024 at 13,391.71 points, an increase compared to the previous year. Even with the economic effects of the global coronavirus (COVID-19) pandemic, 2021 had the highest point of the index in the past two decades. What is Dow Jones Composite Index? The Dow Jones Composite Index is one of the indices from the Dow Jones index family. It is composed of 65 leading U.S. companies: 30 stocks forming the Dow Jones Industrial Average index, 20 stocks from the Dow Jones Transportation index and 15 stocks from the Dow Jones Utility Average index. Importance of stock indices A stock market index shows an average performance of companies from a given section of the market. It is usually a weighted average, meaning that such factors as price of companies or their market capitalization are taken into consideration when calculating the index value. Stock indices are very useful for the financial market participants, as they instantly show the sentiments prevailing on a given market. They are also commonly used as a benchmark against portfolio performance, showing if a given portfolio has outperformed, or underperformed the market.

The Dow Jones Industrial Average is (DJIA) is possibly the most well-known and commonly used stock index in the United States. It is a price-weighted index that assesses the stock prices of 30 prominent companies, whose combined prices are then divided by a regularly-updated divisor (0.15199 in February 2021), which gives the index value. The companies included are rotated in and out on a regular basis; as of mid-2022, the longest mainstay on the list is Procter & Gamble, which was added in 1932; whereas Amgen, Salesforce, and Honeywell were all added in 2020. As one of the oldest indices for stock market analysis, the impact of major events, recessions, and economic shocks or booms can be tracked and contextualized over longer periods of time.

Due to inflation, unadjusted figures appear to be more sporadic in recent years, however the greatest fluctuations came in the earliest years of the index. In the given period, the greatest decline came in the wake of the Wall Street Crash in 1929; by 1932 average values had fallen to just one fifth of their 1929 average, from roughly 314 to 65.

The dataset consists of daily data from US Dow Jones for 501 large companies, over the time span 2010-2016, while monthly publicly available indexes are also used.

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.

Summary statistics of realized opportunity cost and related statistics for Dow 30 stocks, aggregated over the 252 trading days in 2016.

The main stock market index of United States, the US500, rose to 6718 points on October 3, 2025, gaining 0.04% from the previous session. Over the past month, the index has climbed 3.31% and is up 16.80% 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 October of 2025.

Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in calendar year 2016 from the vantage point of a single and fixed frame of reference. We find that inefficiencies created in part by the fragmentation of the equity marketplace are relatively common and persist for longer than what physical constraints may suggest. Information feeds reported different prices for the same equity more than 120 million times, with almost 64 million dislocation segments featuring meaningfully longer duration and higher magnitude. During this period, roughly 22% of all trades occurred while the SIP and aggregated direct feeds were dislocated. The current market configuration resulted in a realized opportunity cost totaling over $160 million, a conservative estimate that does not take into account intra-day offsetting events.

Dow's annual revenue was $42.96 B in fiscal year 2024. The annual revenue decreased -$1.66 B from $44.62 B (in 2023) to $42.96 B (in 2024), representing a -3.72% year-over-year decline.

United States Index: Dow Jones: Basic Resources data was reported at 159.820 31Dec1991=100 in Nov 2018. This records a decrease from the previous number of 161.960 31Dec1991=100 for Oct 2018. United States Index: Dow Jones: Basic Resources data is updated monthly, averaging 197.970 31Dec1991=100 from Aug 2005 (Median) to Nov 2018, with 160 observations. The data reached an all-time high of 428.680 31Dec1991=100 in Jun 2008 and a record low of 93.430 31Dec1991=100 in Jan 2016. United States Index: Dow Jones: Basic Resources data remains active status in CEIC and is reported by Dow Jones. The data is categorized under Global Database’s United States – Table US.Z015: Dow Jones: Indexes.

New York Stock Exchange: Index: Dow Jones US Basic Materials Index data was reported at 533.990 NA in Apr 2025. This records a decrease from the previous number of 549.090 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Basic Materials Index data is updated monthly, averaging 386.685 NA from Jul 2013 (Median) to Apr 2025, with 142 observations. The data reached an all-time high of 615.910 NA in Sep 2024 and a record low of 255.100 NA in Jan 2016. New York Stock Exchange: Index: Dow Jones US Basic Materials 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: New York Stock Exchange: Dow Jones: Monthly.

United States Index: Dow Jones: Pharmaceuticals data was reported at 502.480 31Dec1991=100 in Jun 2018. This records an increase from the previous number of 492.300 31Dec1991=100 for May 2018. United States Index: Dow Jones: Pharmaceuticals data is updated monthly, averaging 290.200 31Dec1991=100 from Aug 2005 (Median) to Jun 2018, with 155 observations. The data reached an all-time high of 535.630 31Dec1991=100 in Jul 2016 and a record low of 183.680 31Dec1991=100 in Feb 2009. United States Index: Dow Jones: Pharmaceuticals data remains active status in CEIC and is reported by Dow Jones. The data is categorized under Global Database’s USA – Table US.Z015: Dow Jones: Indexes.

A daily data ranging from January 2014 until December 2018 is employed. The period between January, 1, 2014 until November 7, 2016 refers to the pre-election period. The period ranging from November 8, 2016, until December, 31 2018 defines the post-election period. Four U.S stock price indices are retrieved from DataStream: The standard and Poor’s 500 index (S&P 500) covers the performance of 500 largest capitalization stocks. The Dow Jones Industrial Average (DJIA) index tracks the prices of the top 30 US companies. The NASDAQ 100 measures the performance of the 100 largest non-financial stocks traded on NASDAQ. The Russell 2000 index covers the performance of 2.000 lowest capitalization stocks. A daily political risk index is calculated for each period using Google trends and the principal component analysis.

Of the approximately 120 million DSs observed, more than 54% of them have a duration that would allow them to be considered actionable, and about 2.4% of them are both actionable and feature a minimum magnitude greater than $0.01. This makes the magnitude of the realized opportunity cost even more remarkable. Additionally, note that observed durations of “0” are the result of DSs that begin and end within the same microsecond, the maximum precision used for the majority of market data timestamps.

United States Index: Dow Jones: Food Producers data was reported at 365.680 31Dec1991=100 in Jun 2018. This records an increase from the previous number of 347.290 31Dec1991=100 for May 2018. United States Index: Dow Jones: Food Producers data is updated monthly, averaging 213.790 31Dec1991=100 from Aug 2005 (Median) to Jun 2018, with 155 observations. The data reached an all-time high of 410.320 31Dec1991=100 in Jul 2016 and a record low of 137.360 31Dec1991=100 in Feb 2009. United States Index: Dow Jones: Food Producers data remains active status in CEIC and is reported by Dow Jones. The data is categorized under Global Database’s USA – Table US.Z015: Dow Jones: Indexes.

These propagation delays form the basis for estimates of the duration required for a dislocation segment to be considered actionable, though these figures do not account for any computing delays and thus are lower bounds for the definition of actionable.

Statistics 8–10 indicate that trades occurring during dislocations involve approximately 5% more value per trade on average than those that occur while feeds are synchronized. The values reported above are sums of daily observations, except for statistics 8–10, and are conservative estimates of the true, unobserved quantities since positive (favoring the SIP) and negative (favoring the direct feeds) ROC can cancel in summary calculations.

The statistic shows the worst days of the Dow Jones Industrial Average index from 1897 to 2024. The worst day in the history of the index was ****************, when the index value decreased by ***** percent. The largest single day loss in points was on ***********.

The collected tweets and Earnings Announcements (EA) cover the period of three years, from June 1, 2013 to June 3, 2016. Companies are ordered by the total number of tweets collected. For each company, there is the sentiment distribution, market capitalization, and the prevailing timing of EAs with respect to the NYSE trading hours. Each company issues four EAs per year, therefore there is a total of 360 EAs (30 companies, three years, four EAs per year)1.

Actually, I prepare this dataset for students on my Deep Learning and NLP course.

But I am also very happy to see kagglers play around with it.

Have fun!

Description:

There are two channels of data provided in this dataset:

1. News data: I crawled historical news headlines from Reddit WorldNews Channel (/r/worldnews). They are ranked by reddit users' votes, and only the top 25 headlines are considered for a single date. (Range: 2008-06-08 to 2016-07-01)

2. Stock data: Dow Jones Industrial Average (DJIA) is used to "prove the concept". (Range: 2008-08-08 to 2016-07-01)

I provided three data files in .csv format:

1. RedditNews.csv: two columns The first column is the "date", and second column is the "news headlines". All news are ranked from top to bottom based on how hot they are. Hence, there are 25 lines for each date.

2. DJIA_table.csv: Downloaded directly from Yahoo Finance: check out the web page for more info.

3. Combined_News_DJIA.csv: To make things easier for my students, I provide this combined dataset with 27 columns. The first column is "Date", the second is "Label", and the following ones are news headlines ranging from "Top1" to "Top25".

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To my students:

I made this a binary classification task. Hence, there are only two labels:

"1" when DJIA Adj Close value rose or stayed as the same;

"0" when DJIA Adj Close value decreased.

For task evaluation, please use data from 2008-08-08 to 2014-12-31 as Training Set, and Test Set is then the following two years data (from 2015-01-02 to 2016-07-01). This is roughly a 80%/20% split.

And, of course, use AUC as the evaluation metric.

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To all kagglers:

Please upvote this dataset if you like this idea for market prediction.

If you think you coded an amazing trading algorithm,

friendly advice

do play safe with your own money :)

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Feel free to contact me if there is any question~

And, remember me when you become a millionaire :P

Note: If you'd like to cite this dataset in your publications, please use:

Sun, J. (2016, August). Daily News for Stock Market Prediction, Version 1. Retrieved [Date You Retrieved This Data] from https://www.kaggle.com/aaron7sun/stocknews.