Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-07-21 about VIX, volatility, stock market, and USA.

Graph and download economic data for CBOE S&P 500 3-Month Volatility Index (VXVCLS) from 2007-12-04 to 2025-07-18 about VIX, volatility, 3-month, stock market, and USA.

CBOE Volatility Index (VIX) time-series dataset including daily open, close, high and low. The CBOE Volatility Index (VIX) is a key measure of market expectations of near-term volatility conveyed by...

United States - CBOE Volatility : VIX was 16.41000 Index in July 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 July of 2025.

Download Historical CBOE S&P 500 3-Month Volatility Index Indicies Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

Graph and download economic data for CBOE Russell 2000 Volatility Index (RVXCLS) from 2004-01-02 to 2025-07-18 about VIX, volatility, stock market, and USA.

Graph and download economic data for CBOE DJIA Volatility Index (VXDCLS) from 1997-10-07 to 2025-07-18 about VIX, volatility, stock market, and USA.

United States - CBOE S&P 100 Volatility : VXO (DISCONTINUED) was 17.87000 Index in September of 2021, according to the United States Federal Reserve. Historically, United States - CBOE S&P 100 Volatility : VXO (DISCONTINUED) reached a record high of 150.19000 in October of 1987 and a record low of 6.32000 in July of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE S&P 100 Volatility : VXO (DISCONTINUED) - last updated from the United States Federal Reserve on July of 2025.

United States - CBOE S&P 500 3-Month Volatility was 19.58000 Index in July 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 July of 2025.

Graph and download economic data for CBOE Crude Oil ETF Volatility Index (OVXCLS) from 2007-05-10 to 2025-07-18 about ETF, VIX, volatility, crude, oil, stock market, and USA.

United States - CBOE Gold ETF Volatility was 20.41000 Index in June of 2025, according to the United States Federal Reserve. Historically, United States - CBOE Gold ETF Volatility reached a record high of 64.53000 in October of 2008 and a record low of 8.88000 in May of 2019. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE Gold ETF Volatility - last updated from the United States Federal Reserve on June of 2025.

United States - CBOE NASDAQ 100 Volatility was 18.67000 Index in July of 2025, according to the United States Federal Reserve. Historically, United States - CBOE NASDAQ 100 Volatility reached a record high of 80.64000 in November of 2008 and a record low of 10.31000 in March of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE NASDAQ 100 Volatility - last updated from the United States Federal Reserve on July of 2025.

VIX Daily Price Data

Overview

Contains historical data of the VIX Volatility Index from 2000 - 2025. The data is obtained from the yfinance api created by yahoo finance and contains the daily price data for the VIX.

The dataset contains the daily Open, Close, High, and Low of the VIX.

Columns Open: Starting price level of VIX for the day Close: Final price level of VIX for the day High: Highest price level of VIX for the day Low: Lowest price level of VIX for the day

The VIX is an index that measures near term volatility expectations for the S&P 500 gathered from SPX options data. VIX was created and maintained by CBOE.

Uses

This data can be used to train models on predicting the market's volatility forecasts. The VIX can also be compared to the realized historical volatility over a period of time.

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 Volatility Index Options & Futures Prediction

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

United States - CBOE EuroCurrency ETF Volatility was 10.68000 Index in March of 2025, according to the United States Federal Reserve. Historically, United States - CBOE EuroCurrency ETF Volatility reached a record high of 30.66000 in October of 2008 and a record low of 4.13000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE EuroCurrency ETF Volatility - last updated from the United States Federal Reserve on June 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.

Buy or Sell: CBOE Volatility Index 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

United States - CBOE Emerging Markets ETF Volatility was 17.97000 Index in July of 2025, according to the United States Federal Reserve. Historically, United States - CBOE Emerging Markets ETF Volatility reached a record high of 92.46000 in March of 2020 and a record low of 13.11000 in June of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE Emerging Markets ETF Volatility - last updated from the United States Federal Reserve on July of 2025.

United States - CBOE DJIA Volatility was 15.71000 Index in July 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 July of 2025.

This dataset contains historical daily values of the CBOE Volatility Index (VIX), including open, high, low, and closing prices, starting from January 2, 1990.

United States - CBOE Crude Oil ETF Volatility was 32.80000 Index in July of 2025, according to the United States Federal Reserve. Historically, United States - CBOE Crude Oil ETF Volatility reached a record high of 325.15000 in April of 2020 and a record low of 14.50000 in June of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - CBOE Crude Oil ETF Volatility - last updated from the United States Federal Reserve on July of 2025.