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.

CBOE Cboe Global Markets Inc. Common Stock

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

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-03-24 about VIX, volatility, stock market, and USA.

United States - CBOE DJIA Volatility was 15.38000 Index in March of 2025, according to the United States Federal Reserve. Historically, United States - CBOE DJIA Volatility reached a record high of 74.60000 in November of 2008 and a record low of 2.71000 in July of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE DJIA Volatility - last updated from the United States Federal Reserve on March of 2025.

Graph and download economic data for CBOE S&P 500 3-Month Volatility Index (VXVCLS) from 2007-12-04 to 2025-03-24 about VIX, volatility, 3-month, stock market, and USA.

United States - CBOE S&P 500 3-Month Volatility was 20.35000 Index in March of 2025, according to the United States Federal Reserve. Historically, United States - CBOE S&P 500 3-Month Volatility reached a record high of 72.98000 in March of 2020 and a record low of 11.85000 in October of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE S&P 500 3-Month Volatility - last updated from the United States Federal Reserve on March of 2025.

As of April 2024, the combined average monthly turnover of the three main U.S. equities market operators - the New York Stock Exchange (NYSE), the Nasdaq, and Chicago Board Options Exchange (CBOE) Global Markets - amounted to around 6.6 trillion U.S. dollars. However, the largest share of total equity trades in the United States was held by off-exchange transactions.

Graph and download economic data for CBOE Crude Oil ETF Volatility Index (OVXCLS) from 2007-05-10 to 2025-03-25 about ETF, VIX, volatility, crude, oil, stock market, and USA.

United States - CBOE Volatility : VIX was 17.48000 Index in March of 2025, according to the United States Federal Reserve. Historically, United States - CBOE Volatility : VIX reached a record high of 82.69000 in March of 2020 and a record low of 9.14000 in November of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE Volatility : VIX - last updated from the United States Federal Reserve on March of 2025.

Graph and download economic data for CBOE Gold ETF Volatility Index (GVZCLS) from 2008-06-03 to 2025-03-25 about ETF, VIX, gold, volatility, stock market, and USA.