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.

Venezuela's main stock market index, the IBC, rose to 1554 points on December 2, 2025, gaining 0.15% from the previous session. Over the past month, the index has declined 2.61%, though it remains 1,361.02% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Venezuela. Venezuela Stock Market (IBVC) - values, historical data, forecasts and news - updated on December of 2025.

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.

S&P 500 Stock Prices

Historical stock market data for current S&P 500 companies, from 2014-2017. Each record represents a single day of trading, and includes the ticker name, volume, high, low, open and close prices.

Recommended Analysis

Which date in the sample saw the largest overall trading volume? On that date, which two stocks were traded most?

On which day of the week does volume tend to be highest? Lowest?

On which date did Amazon (AMZN) see the most volatility, measured by the difference between the high and low price?

If you could go back in time and invest in one stock from 1/2/2014 - 12/29/2017, which would you choose? What % gain would you realize?

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 statistic shows the ten leading stock exchanges worldwide in 2017*, by capital raised. At the New York Stock Exchange, the issuing volume between January and August 2017 amounted to 22.2 billion U.S. dollars.

United States US: Market Capitalization: Listed Domestic Companies data was reported at 32,120.703 USD bn in 2017. This records an increase from the previous number of 27,352.201 USD bn for 2016. United States US: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 11,322.354 USD bn from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 32,120.703 USD bn in 2017 and a record low of 1,263.561 USD bn in 1981. United States US: 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 United States – Table US.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: Stock market capitalization, billion USD: The latest value from 2018 is 2365.95 billion U.S. dollars, a decline from 2749.31 billion U.S. dollars in 2017. In comparison, the world average is 918.86 billion U.S. dollars, based on data from 76 countries. Historically, the average for France from 1975 to 2018 is 966.7 billion U.S. dollars. The minimum value, 27.4 billion U.S. dollars, was reached in 1976 while the maximum of 2749.31 billion U.S. dollars was recorded in 2017.

Context

The dataset presentes changes of some stocks, like Google,Apple,Amazon,Alibaba,Facebook,Tencent.

Content

It contains the date, the start price, the end price and other informations in 2017.1-2018.1; Fetched it from Yahoo finance used pandas_reader.

Acknowledgements

Thanks everyone encouraging me.

Inspiration

How do you analyze a dataset by python?

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.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 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.

Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on December of 2025.

The number of active clients on the stock market, or those who made at least one deal over the past month, in Russia reached around *** million in December 2022. Thus, the figure saw a decrease from the corresponding month of the previous year, when it exceeded *** million. Between December 2017 and December 2021, the number of active clients steadily increased.

Between July 2017 and December 2022, the market capitalization of the Italian footwear and apparel company Geox on the Milan Stock Exchange experienced a dramatic overall decrease. In fact, Geox's market cap started at around *** million euros as of July 2017 and closed at around *** million euros as of December 2022. Market capitalization of Geox reached its lowest point in October 2020, when it dropped below *** million euros.

Datasets contain a sample of the Dow Jones Industrial Average (DJIA) index values, as well as stock prices of the companies that form the DJIA today. A little about this stock market index: https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average Daily DJIA index values and stock prices are taken from March 01, 2017 to March 19, 2020. All prices are the closing prices (the last price at which the stock traded during the regular trading day). It should be noted that stock prices Dow Inc. available only from March 20, 2019, the remaining price values are NaN (Dow Inc. was added to the DJIA since April 02, 2019).

This dataset contains the data provided Michael Lachanski and Steven Pav to reproduce their paper Shy of the Character Limit: “Twitter Mood Predicts the Stock Market” Revisited. Since they are unable to share the raw tweets, this dataset contains summary statistics for the Twitter data and the Down Jones Index.

If you use this data in your work, please cite the following paper:

Lachanski, M., & Pav, S. (2017). Shy of the Character Limit:" Twitter Mood Predicts the Stock Market" Revisited. Econ Journal Watch, 14(3), 302.

Dataset contents

The file calm_sentiment_data.csv contains Twitter sentiment data for the 'calm' sentiment, aligned with returns of the DJI (the Dow Jones Index) GSPC (the S&P 500 index). The fields consist of:

• date : the date of the observed Twitter sentiment data. The data are observable by 23:59:59 EST of the given date.
• tone : the tone sentiment series.
• calm : the calm sentiment series.
• tone_Z10 : the normalized tone variable, using k=10. This is essentially a centered Z-score of tone over 21 observations.
• tone_Z1 : the normalized tone variable, using k=1. This is essentially a centered Z-score of tone over 3 (!) observations.
• DJI : the closing value of the DJI index for the given day. Will take value of NA when the market is closed. Early closes are treated as normal market days. The DJI data are source from Yahoo finance via the quantmod package.
• DJI_volume_k : the volume of the DJI index for the given day, in thousands. This may be useful for data QA, for example. The volume is NA when the market is closed.
• DJI_forward_return : this is a one market period relative 'return' of the DJI index. A value of 0.01, for example, corresponds to a 1% increase in the DJI index. This is a forward return, meaning it is the return from the close of the given day to the close of the next market day, and could be approximately captured by a long holder in the index. (Were that possible; an index is not an ETF.) The return is NA when the market is closed. Note that there is an overlap in information between the Twitter sentiment series and the forward return: the sentiment data is only observable just before midnight EST, while one would have to invest just before 4PM EST to capture the forward return.
• GSPC : the closing value of the GSPC index for the given day. Will take value of NA when the market is closed. Early closes are treated as normal market days. The GSPC data are source from Yahoo finance via the quantmod package. While the original paper does not make claims regarding Twitter mood and the GSPC series, it represents broad market returns and makes a suitable target for a putative forecast of the market by sentiment.
• GSPC_volume_k : the volume of the GSPC index for the given day, in thousands.
• GSPC_forward_return : the one market period relative 'return' of the GSPC index. This is a forward_return, meaning it is the return from the close of the given day to the close of the next market day. The return is NA when the market is closed.

United States US: Stocks Traded: Turnover Ratio of Domestic Shares data was reported at 116.078 % in 2017. This records an increase from the previous number of 94.719 % for 2016. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data is updated yearly, averaging 114.857 % from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 407.630 % in 2008 and a record low of 51.444 % in 1991. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.; ; 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.

Norway: Stock market value traded w/o top 10 firms, % of total value traded: The latest value from 2017 is 59.83 percent, an increase from 37.27 percent in 2016. In comparison, the world average is 50.89 percent, based on data from 36 countries. Historically, the average for Norway from 1999 to 2017 is 31.41 percent. The minimum value, 6.69 percent, was reached in 2011 while the maximum of 59.83 percent was recorded in 2017.

Pakistan's main stock market index, the KSE 100, fell to 167838 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has climbed 3.09% and is up 60.52% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Pakistan. Pakistan Stock Market (KSE100) - values, historical data, forecasts and news - updated on December of 2025.

This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables".

This table contains 25 series, with data for years 1956 - present (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Toronto Stock Exchange Statistics (25 items: Standard and Poor's/Toronto Stock Exchange Composite Index; high; Standard and Poor's/Toronto Stock Exchange Composite Index; close; Toronto Stock Exchange; oil and gas; closing quotations; Standard and Poor's/Toronto Stock Exchange Composite Index; low ...).