The Nasdaq Composite Index increased overall following the global financial crisis of 2008. In 2022, the closing year-end value of the Nasdaq Composite Index was *********, a significant decrease compared to 2021. In the following years, however, the Index recovered and grew, closing at ********* points as of December 31, 2024.

The annual returns of the Nasdaq 100 Index from 1986 to 2024. fluctuated significantly throughout the period considered. The Nasdaq 100 index saw its lowest performance in 2008, with a return rate of ****** percent, while the largest returns were registered in 1999, at ****** percent. As of June 11, 2024, the rate of return of Nasdaq 100 Index stood at ** percent. The Nasdaq 100 is a stock market index comprised of the 100 largest and most actively traded non-financial companies listed on the Nasdaq stock exchange. How has the Nasdaq 100 evolved over years? The Nasdaq 100, which was previously heavily influenced by tech companies during the dot-com boom, has undergone significant diversification. Today, it represents a broader range of high-growth, non-financial companies across sectors like consumer services and healthcare, reflecting the evolving landscape of the global economy. The annual development of the Nasdaq 100 recently has generally been positive, except for 2022, when the NASDAQ experienced a decline due to worries about escalating inflation, interest rates, and regulatory challenges. What are the leading companies on Nasdaq 100? In August 2023, ***** was the largest company on the Nasdaq 100, with a market capitalization of **** trillion euros. Also, ****************************************** were among the five leading companies included in the index. Market capitalization is one of the most common ways of measuring how big a company is in the financial markets. It is calculated by multiplying the total number of outstanding shares by the current market price.

The main stock market index of United States, the US500, fell to 6445 points on August 18, 2025, losing 0.07% from the previous session. Over the past month, the index has climbed 2.22% and is up 14.93% 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 August of 2025.

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.

Graph and download economic data for Nasdaq-100 Total Return INR (NASDAQXNDXINR) from 2022-02-22 to 2025-08-04 about NASDAQ, return, indexes, and USA.

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.

NASDAQ Composite Index NASDAQ Composite Index

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

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.

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 Nasdaq Composite index fluctuated significantly in recent years, despite overall increasing more than ******* between January 2018 and December 2021. In particular, during 2022 the index decreased due to a generalized disruption in the financial markets caused by the Russia-Ukraine war. As of the end of December 2024, the Nasdaq Composite index reached a value of *********, an increase when compared to the previous month.

NASDAQ: Index: Total Return: NASDAQ US Benchmark Fertilizers Index data was reported at 1,105.180 NA in Apr 2025. This records an increase from the previous number of 1,069.890 NA for Mar 2025. NASDAQ: Index: Total Return: NASDAQ US Benchmark Fertilizers Index data is updated monthly, averaging 1,241.833 NA from Sep 2020 (Median) to Apr 2025, with 56 observations. The data reached an all-time high of 2,012.050 NA in Mar 2022 and a record low of 927.390 NA in Oct 2020. NASDAQ: Index: Total Return: NASDAQ US Benchmark Fertilizers 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: NASDAQ: Total Return: Monthly.

Stock market return (%, year-on-year) in United States was reported at 32.65 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

NASDAQ: Index: Total Return: NASDAQ US Benchmark Gold Mining Index data was reported at 1,275.380 NA in Apr 2025. This records an increase from the previous number of 1,174.660 NA for Mar 2025. NASDAQ: Index: Total Return: NASDAQ US Benchmark Gold Mining Index data is updated monthly, averaging 811.805 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,593.040 NA in Mar 2022 and a record low of 325.050 NA in Sep 2015. NASDAQ: Index: Total Return: NASDAQ US Benchmark Gold Mining 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: NASDAQ: Total Return: Monthly.

United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Security Services Index data was reported at 1,046.690 NA in Apr 2025. This records an increase from the previous number of 1,017.410 NA for Mar 2025. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Security Services Index data is updated monthly, averaging 954.020 NA from Sep 2020 (Median) to Apr 2025, with 56 observations. The data reached an all-time high of 1,197.710 NA in Jun 2021 and a record low of 679.840 NA in Jun 2022. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Security Services 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: NASDAQ: Net Total Return: Monthly.

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 Industrial Average (DJI) index increased overall between January 2022 and April 2024. Between January 4 and June 17, 2022, the index dropped nearly ***** points. It then managed to recover to ********* points as of August 16, 2022, but started a sharp decrease again afterwards. As of March 3, 2025, the index stood at ********* points.

Malawi was the African country with the best-performing stock market in 2022. That year, the Malawian stock exchange grew by around ** percent compared to the previous year. Egypt and Zambia followed with a performance of **** percent and **** percent, respectively. On the other hand, the stock market in Kenya and Morocco contacted by almost ** and ** percent in 2022, respectively.

United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Entertainment Index data was reported at 1,431.670 NA in Apr 2025. This records an increase from the previous number of 1,290.860 NA for Mar 2025. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Entertainment Index data is updated monthly, averaging 1,026.946 NA from Sep 2020 (Median) to Apr 2025, with 56 observations. The data reached an all-time high of 1,431.670 NA in Apr 2025 and a record low of 588.330 NA in Jun 2022. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Entertainment 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: NASDAQ: Total Return: Monthly.

United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Forms and Bulk Printing Services Index data was reported at 550.570 NA in Apr 2025. This records a decrease from the previous number of 599.850 NA for Mar 2025. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Forms and Bulk Printing Services Index data is updated monthly, averaging 810.115 NA from Mar 2021 (Median) to Apr 2025, with 50 observations. The data reached an all-time high of 1,088.040 NA in Jun 2021 and a record low of 450.840 NA in Sep 2022. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Forms and Bulk Printing Services 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: NASDAQ: Net Total Return: Monthly.

Graph and download economic data for Nasdaq-100 Notional Net Total Return INR (NASDAQXNDXNNRINR) from 2022-02-22 to 2025-08-04 about NASDAQ, return, Net, indexes, and USA.

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.

Trading Signals (NASDAQ Composite Index 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