United States - NASDAQ 100 was 23219.86000 Index in July of 2025, according to the United States Federal Reserve. Historically, United States - NASDAQ 100 reached a record high of 23219.86000 in July of 2025 and a record low of 128.43000 in October of 1987. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - NASDAQ 100 - last updated from the United States Federal Reserve on July of 2025.

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 100: A Market in Flux, But Some Sectors to Profit From

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

Historical AI model predictions and analysis for Nasdaq-100 ETF stock across multiple timeframes and confidence levels

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.

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 100 Futures

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

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.

FTSE 100: Where to Next?

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 FTSE 100 index is expected to experience moderate growth, driven by positive economic indicators and the easing of COVID-19 restrictions. However, concerns regarding inflation, geopolitical tensions, and the potential impact of interest rate hikes pose risks to the index's performance.

United Kingdom's main stock market index, the GB100, rose to 9177 points on August 14, 2025, gaining 0.13% from the previous session. Over the past month, the index has climbed 2.67% and is up 9.94% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on August of 2025.

Turkey's main stock market index, the BIST 100, rose to 10846 points on August 15, 2025, gaining 0.19% from the previous session. Over the past month, the index has climbed 7.15% and is up 10.42% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Turkey. Turkey Stock Market - values, historical data, forecasts and news - updated on August of 2025.

Pakistan's main stock market index, the KSE 100, fell to 146492 points on August 15, 2025, losing 0.03% from the previous session. Over the past month, the index has climbed 7.41% and is up 87.70% 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 August of 2025.

Prices for US 100 Tech Index including live quotes, historical charts and news. US 100 Tech Index was last updated by Trading Economics this August 17 of 2025.

Sweden's main stock market index, the Stockholm, fell to 2626 points on August 18, 2025, losing 0.57% from the previous session. Over the past month, the index has climbed 2.90% and is up 3.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Sweden. Sweden Stock Market Index - values, historical data, forecasts and news - updated on August of 2025.

France's main stock market index, the FR40, rose to 7923 points on August 15, 2025, gaining 0.67% from the previous session. Over the past month, the index has climbed 2.61% and is up 6.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on August of 2025.

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.

QQQX Nuveen NASDAQ 100 Dynamic Overwrite Fund Shares of Beneficial Interest

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

Poland's main stock market index, the WIG, fell to 109367 points on August 14, 2025, losing 1.28% from the previous session. Over the past month, the index has climbed 3.68% and is up 29.14% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Poland. Warsaw Stock Exchange WIG Index - values, historical data, forecasts and news - updated on August of 2025.

I have created this dataset to showcase the use of predictive modeling using the stock market as a case study. This dataset is designed to help and predict tomorrow's Amazon stock price. If you want to get the most updated dataset you will need to pull them in real time. I have shared my code to pull data using Yahoo Finance API and preprocess it in Data Analytics for Fun Github Repository

The uploaded dataset is for Jan 11, 2021.

What are the columns?

yes_changeP: Yesterday Amazon's stock price change lastweek_changeP: Last week Amazon's stock price change dow_yes_changeP: Yesterday Dow Jones change dow_lastweek_changeP: Last Week Dow Jones change nasdaq_yes_changeP: Yesterday NASDAQ 100 change nasdaq_lastweek_changeP: Last Week NASDAQ 100 change today_changeP: Today Amazon's stock price change

To learn more about the dataset and see a very simple prediction model applied to the dataset you may watch this YouTube Video where I have explained the dataset and also prediction: A Taste for Prediction: Predict Tomorrow's Amazon Stock Price

Japan's main stock market index, the JP225, rose to 43366 points on August 15, 2025, gaining 1.68% from the previous session. Over the past month, the index has climbed 9.34% and is up 13.93% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on August of 2025.

Stay updated with Market Research Intellect's Stock Market Report, valued at USD 100 trillion in 2024, projected to reach USD 150 trillion by 2033 with a CAGR of 4.5% (2026-2033).

Germany's main stock market index, the DE40, fell to 24359 points on August 15, 2025, losing 0.07% from the previous session. Over the past month, the index has climbed 1.46% and is up 32.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on August of 2025.

Historical AI model predictions and analysis for ProShares UltraPro QQQ stock across multiple timeframes and confidence levels