The value of the DJIA index amounted to ********* at the end of February 2026, 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 2016-03-28 to 2026-03-27 about stock market, average, industry, and USA.

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 main stock market index of United States, the US500, fell to 6369 points on March 27, 2026, losing 1.67% from the previous session. Over the past month, the index has declined 7.45%, though it remains 14.12% higher than a year ago, 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 March of 2026.

Context

Dow Jones 30 is a price-weighted measurement stock market index of 30 prominent companies listed on stock exchanges in the United States. It is one of the most concise Indices as compared to other comprehensive ones such as NASDAQ or S&P 500.

The value index can be sum of the stock prices of the companies included in the index, divided by a factor which is currently approximately 0.152. The factor is changed whenever a constituent company undergoes a stock split so that the value of the index is unaffected by the stock split.

Content

In the dataset, You'll find stock prices of 16 major companies which are listed in DOW JONES 30 Index before Apr 1, 1999 (Obviously there are 14 others which they've replaced others over time and were added in the index after the said date)

Date: Simply the data in m/d/yyyy format (which works in the US)

MMM to Walt Disney: Average stock price of the day of the corresponding companies

DJIA: "Dow Jones Industrial Average" which can be said the target column of the dataset. It is the pool in which all the 30 stocks have their influence. Target can be seen as how much impact each and every stock lays on the pool.

Acknowledgement

The data is obtained from the Moneycontrol website.

Inspiration

Predicting the influence of major stocks on one of the most weight carrying indices of the world.

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.

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 Dow-Jones Industrial Stock Price Index for United States (M1109BUSM293NNBR) from Dec 1914 to Dec 1968 about stock market, industry, price index, indexes, price, and USA.

Tick (Bids | Asks | Trades | Settle) sample data for DJ Industrial Average - Index DJI timestamped in Chicago time

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.

Throughout the 1920s, prices on the U.S. stock exchange rose exponentially, however, by the end of the decade, uncontrolled growth and a stock market propped up by speculation and borrowed money proved unsustainable, resulting in the Wall Street Crash of October 1929. This set a chain of events in motion that led to economic collapse - banks demanded repayment of debts, the property market crashed, and people stopped spending as unemployment rose. Within a year the country was in the midst of an economic depression, and the economy continued on a downward trend until late-1932.

It was during this time where Franklin D. Roosevelt (FDR) was elected president, and he assumed office in March 1933 - through a series of economic reforms and New Deal policies, the economy began to recover. Stock prices fluctuated at more sustainable levels over the next decades, and developments were in line with overall economic development, rather than the uncontrolled growth seen in the 1920s. Overall, it took over 25 years for the Dow Jones value to reach its pre-Crash peak.

Prices for United States Stock Market Index (US30) including live quotes, historical charts and news. United States Stock Market Index (US30) was last updated by Trading Economics this March 28 of 2026.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

The Dow Jones Industrial Average

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

There have been ups and downs in the history of the Dow Jones Industrial Average index (DJIA). Some years brought as much as ** percent of decrease in its value. Great Recession, however, took the largest toll on the Dow. In 1931, the index lost ***** percent of its value.

Index history

Dow Jones Industrial Average index (DJIA) is one of the most important stock market indices worldwide. It was created in 1896 by Charles Dow and Edward Jones. DJIA is the second oldest U.S. stock index after the Dow Jones Transportation Average, which was established in 1984.

Index components

DJIA reflects the performance of thirty large U.S. publicly traded companies. When the index was created, it was primarily composed of industrial companies, hence the index name. With time, the economic situation in the U.S. has changed and apart from industrial companies, which played a huge role in the market in the **** and the beginning of the **** century, also companies from other leading industries were incorporated into the index. At present, the DJIA index is composed of most renowned U.S. corporations, such as Coca Cola, Microsoft or Walt Disney.

Tick (Bids | Asks | Trades | Settle) sample data for DJIA Mini $5 Index YM timestamped in Chicago time

Graph and download economic data for NASDAQ Composite (NASDAQCOM) from 1971-02-05 to 2026-03-25 about composite, stock market, NASDAQ, indexes, and USA.

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)

Sources

The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.

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.

Russia's main stock market index, the MOEX, fell to 2786 points on March 27, 2026, losing 1.31% from the previous session. Over the past month, the index has declined 1.75% and is down 7.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on March of 2026.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Should You Buy Dow Jones Industrial Average Index Right Now? (Stock Forecast)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data