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.

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 Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

The Dow Jones Industrial Average (DJIA) is a stock market index used to analyze trends in the stock market. While many economists prefer to use other, market-weighted indices (the DJIA is price-weighted) as they are perceived to be more representative of the overall market, the Dow Jones remains one of the most commonly-used indices today, and its longevity allows for historical events and long-term trends to be analyzed over extended periods of time. Average changes in yearly closing prices, for example, shows how markets developed year on year. Figures were more sporadic in early years, but the impact of major events can be observed throughout. For example, the occasions where a decrease of more than 25 percent was observed each coincided with a major recession; these include the Post-WWI Recession in 1920, the Great Depression in 1929, the Recession of 1937-38, the 1973-75 Recession, and the Great Recession in 2008.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-12-02 to 2025-12-01 about stock market, average, industry, and USA.

This statistic presents the development of the Dow Jones Industrial Average index from 1986 to 2023. The 2023 year-end value of Dow Jones Industrial Average index amounted to *********. What is the Dow Jones Industrial Average index? Along with the NASDAQ 100 index, the Dow Jones Industrial Average (DJIA) is amongst the most well-known and used stock indexes in the world. DJIA index was created in 1985 by Charles Dow. It is second oldest U.S. index and one of the most important U.S. stock market indices. It reflects the performance of 30 of the most influential U.S. based companies from various industries, such as JPMorgan Chase, IBM and Walt Disney traded on the New York Stock Exchange and the NASDAQ. Performance of the Dow Jones Industrial Average The year that the financial crisis unfolded, 2008, was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the DJIA based on single-day points were registered. On September 29th of 2008, for instance, the Dow had a loss of ****** points, the third largest single-day loss of all times. Since 2008 the index has generally been increasing, registering a high of ********* in 2019 before the economic effects of the global coronavirus (COVID-19) pandemic caused both the largest single-day losses, and largest single-day gains of the DJIA.

The aim of this study is to determine whether the stock indices of some developed and developing countries react similarly to the price movements in the Dow Jones Industrial Average (DJIA). In this study, the impact of DJIA on other indices during the 2008 global financial crisis, was explored by using the Vector Error Correction Model. The data used was analyzed in two periods: (1) the expansionary period; and (2) the contractionary period of the FED's policies. The results of the analysis indicate that the developed and emerging stock markets react differently to the DJIA. The results include important findings for decisions by financial investors and policy makers.

Graph and download economic data for Stock Market Capitalization to GDP for United States (DDDM01USA156NWDB) from 1975 to 2020 about market cap, stock market, capital, GDP, and USA.

The aim of this study is to determine whether the stock indices of some developed and developing countries react similarly to the price movements in the Dow Jones Industrial Average (DJIA). In this study, the impact of DJIA on other indices during the 2008 global financial crisis, was explored by using the Vector Error Correction Model. The data used was analyzed in two periods: (1) the expansionary period; and (2) the contractionary period of the FED's policies. The results of the analysis indicate that the developed and emerging stock markets react differently to the DJIA. The results include important findings for decisions by financial investors and policy makers.

As retail investing continues to reshape global markets, understanding who participates, how they invest, and what influences their decisions has never been more crucial. Stock ownership in the U.S. is reaching levels not seen since before the 2008 crisis, with younger generations, mobile platforms, and new asset classes like ETFs...

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.

The USA: Stock market value traded, percent of GDP: The latest value from 2024 is 145.97 percent, an increase from 134.42 percent in 2023. In comparison, the world average is 30.95 percent, based on data from 68 countries. Historically, the average for the USA from 1975 to 2024 is 127.73 percent. The minimum value, 7.97 percent, was reached in 1977 while the maximum of 319.88 percent was recorded in 2008.

April 9, 2025, saw the largest one-day gain in the history of the Dow Jones Industrial Average (DJIA), follwing Trump's announcement of 90-day delay in the introduction of tariffs imposed on imports from all countries. The second-largest one-day gain occurred on March 24, 2020, with the index increasing ******** points. This occurred approximately two weeks after the largest one-day point loss occurred on March 9, 2020, which was triggered by the growing panic about the coronavirus outbreak worldwide. Index fluctuations The DJIA is an index of ** large companies traded on the New York Stock Exchange. It is one of the numbers that financial analysts watch closely, using it as a bellwether for the United States economy. Seeing when these large gains occur, as well as the largest one-day point losses, gives insight to why these fluctuations may occur. The gains in 2009 are likely adjustments after major losses during the Financial Crisis, but those in 2018 are probably signs of high market volatility. Other leading financial indicators While the DJIA is closely watched, it only gives insight on the performance of thirty leading U.S. companies. An index like the S&P 500, tracking *** companies, can give a more comprehensive overview of the United States economy. Even so, this only reflects investment. Other parts of the economy, such as consumer spending or unemployment rate are not well reflected in stock market indices.

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.

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 November of 2025.

United Kingdom UK: Stocks Traded: Turnover Ratio of Domestic Shares data was reported at 146.431 % in 2008. This records an increase from the previous number of 102.632 % for 2007. United Kingdom UK: Stocks Traded: Turnover Ratio of Domestic Shares data is updated yearly, averaging 40.860 % from Dec 1975 (Median) to 2008, with 34 observations. The data reached an all-time high of 146.431 % in 2008 and a record low of 15.170 % in 1978. United Kingdom UK: 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 Kingdom – Table UK.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.

Description:

This dataset contains historical stock price data for MasterCard (MA) and Visa (V) from June 2008 to June 2024. The data includes daily stock prices with the following columns:

• Date: The date of the recorded stock prices.
• Open_M: Opening price of MasterCard stock.
• High_M: Highest price of MasterCard stock for the day.
• Low_M: Lowest price of MasterCard stock for the day.
• Close_M: Closing price of MasterCard stock.
• Adj Close_M: Adjusted closing price of MasterCard stock.
• Volume_M: Trading volume of MasterCard stock.
• Open_V: Opening price of Visa stock.
• High_V: Highest price of Visa stock for the day.
• Low_y: Lowest price of Visa stock for the day.
• Close_y: Closing price of Visa stock.
• Adj Close_y: Adjusted closing price of Visa stock.
• Volume_y: Trading volume of Visa stock.

Dataset Highlights:

• Comprehensive historical data covering over 15 years.
• Useful for analyzing the stock performance of two major financial - services companies.
• Ideal for time series analysis, financial forecasting, and comparative studies.

Acknowledgments:

The data was sourced and compiled from reliable financial market sources to ensure accuracy and consistency. This dataset is ideal for data scientists, financial analysts, and researchers interested in financial markets and stock price movements.

Usage:

This dataset can be used for: - Time series analysis and forecasting. - Stock market trend analysis. - Comparative analysis of financial services companies. - Educational purposes in finance and data science courses.

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.

Context

Ever since I joined Kaggle, I have been spoilt with countless of high quality datasets and notebooks from many experienced people. I have decided to upload my very first dataset, in order to learn how to upload dataset in Kaggle, as well as an attempt at giving back to the community.

This dataset contains historical price data of Indonesia IDX 30 Stocks. As the list keeps changing, I am using the latest information as of the writing of this text (16 March 2022). Recent changes include removal of 2 large tobacco companies from the IDX 30, which are HMSP (H.M. Sampoerna), and GGRM (Gudang Garam).

Source of IDX 30 Stocks list: https://www.kontan.co.id/indeks-idx30

Content

The dataset consists of 30 csv files. Each csv file contains different stock historical price, with different ticker symbol. The data is obtained using pandas datareader, from Yahoo finance.

As the list of the IDX 30 companies are everchanging, it might include young companies which has undergone recent IPO (such as Bukalapak with ticker symbol BUKA, an E-commerce startup). Hence, despite the data filter indicating starting time of 2006, different companies have different data starting point.

I chose 2006 as data starting point in order to capture the 2008 financial crisis in the data, as well as giving some buffer time before the 2008 market crash.

CSV file formats are as follows:

Index: Date - datetime64 datatype, with format of YYYY-MM-DD (eg: 2008-07-21). Data granularity is daily, and the date excludes days where market is closed. (eg: weekends and public holidays)

Columns descriptions (Price in IDR, as you might have noticed from the number of digits): High - Highest price reached in the day Low - Lowest price reached in the day Open - Price of the stock at market open Close - Price of the stock at market close Volume - Number of stocks traded during the day Adj Close - Price of the stock at market close, adjusted (eg: due to stock splits)

Acknowledgements

My inspiration comes from szrlee which has provided DJIA 30 Stock Time Series. Thank you for the inspiration and sharing of your dataset and how to use pandas datareader. Link to his dataset: https://www.kaggle.com/szrlee/stock-time-series-20050101-to-20171231

Special thanks to Yahoo finance, creator of Pandas-datareader, Kaggle team. Lastly, thank you all members of the Kaggle community, who has provided endless inspirations and wealth of knowledge, as well as continually reminding me how dumb and inexperienced I am as a member of this data community. It drives me to improve myself.

Inspiration

As I am relatively new to stock trading, and currently only has access to the Indonesian stock market, I would love to see anyone giving insights to how the companies behave in comparison with other stocks in different markets. Please note that even some of the largest stocks in Indonesia are merely penny stocks in other markets such as US. (All Indonesian stocks market cap combined is roughly equals to half of Apple's market cap).

Comprehensive 27+ years of daily stock market data for Indian indices (SENSEX & NIFTY 50) and all their constituent companies. This dataset includes OHLCV data along with pre-calculated technical indicators, making it perfect for time series analysis, algorithmic trading strategies, and machine learning applications.

Total Records: 400,000+
Companies: 80 stocks (30 SENSEX + 50 NIFTY 50)
Features: 21 columns per record

Use Cases:

Machine Learning & Prediction:

• Stock price forecasting using LSTM, GRU, or Transformers
• Next-day close price prediction
• Multi-stock portfolio prediction
• Market regime detection (bull/bear markets)

Technical Analysis:

• Backtest trading strategies (RSI, MACD, Moving Average crossovers)
• Identify support/resistance levels
• Bollinger Band squeeze patterns
• Golden Cross / Death Cross detection

Statistical Analysis:

-Correlation analysis between stocks - Volatility clustering analysis - Market crash impact studies (2008 financial crisis, 2020 COVID) - Sectoral performance comparison

Portfolio Optimization:

• Modern Portfolio Theory implementation
• Risk-return optimization
• Diversification analysis
• Sharpe ratio calculations

Education:

• Financial markets course projects
• Time series analysis tutorials
• Data science portfolio projects
• Algorithmic trading education

Company List:

SENSEX 30 Companies:

Adani Enterprises, Asian Paints, Axis Bank, Bajaj Finance, Bajaj Finserv, Bharti Airtel, HDFC Bank, HCL Technologies, Hindustan Unilever, ICICI Bank, IndusInd Bank, Infosys, ITC, Kotak Mahindra Bank, Larsen & Toubro, Mahindra & Mahindra, Maruti Suzuki, Nestle India, NTPC, ONGC, Power Grid Corporation, Reliance Industries, State Bank of India, Sun Pharmaceutical, Tata Consultancy Services, Tata Motors, Tata Steel, Tech Mahindra, Titan Company, UltraTech Cement, Wipro

NIFTY 50 Companies:

All SENSEX 30 companies plus: Adani Ports, Apollo Hospitals, Bajaj Auto, Bharat Petroleum, Britannia Industries, Cipla, Coal India, Divi's Laboratories, Dr. Reddy's Laboratories, Eicher Motors, Grasim Industries, Hero MotoCorp, Hindalco Industries, Hindustan Zinc, JSW Steel, LTIMindtree, Shriram Finance, Tata Consumer Products, Trent

Ticker Conventions: - .BO suffix = Bombay Stock Exchange (BSE) - .NS suffix = National Stock Exchange (NSE)

Citation Policy:

If you use this dataset in your research, please cite:

Indian Stock Market Historical Data - SENSEX & NIFTY 50 (1997-2024)
Kaggle Dataset, November 2024
URL: https://www.kaggle.com/datasets/rockyt07/stock-market-sensex-nifty-all-time-dataset