MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
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)
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.
dt
: Date of observation in YYYY-MM-DD format.vix
: VIX (Volatility Index), a measure of expected market volatility.sp500
: S&P 500 index value, a benchmark of the U.S. stock market.sp500_volume
: Daily trading volume for the S&P 500.djia
: Dow Jones Industrial Average (DJIA), another key U.S. market index.djia_volume
: Daily trading volume for the DJIA.hsi
: Hang Seng Index, representing the Hong Kong stock market.ads
: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.us3m
: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.joblessness
: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).epu
: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.GPRD
: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.prev_day
: Previous day’s S&P 500 closing value, added for lag-based time series analysis.Feel free to use this dataset for academic, research, or personal projects.
The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).
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MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
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)
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.
dt
: Date of observation in YYYY-MM-DD format.vix
: VIX (Volatility Index), a measure of expected market volatility.sp500
: S&P 500 index value, a benchmark of the U.S. stock market.sp500_volume
: Daily trading volume for the S&P 500.djia
: Dow Jones Industrial Average (DJIA), another key U.S. market index.djia_volume
: Daily trading volume for the DJIA.hsi
: Hang Seng Index, representing the Hong Kong stock market.ads
: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.us3m
: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.joblessness
: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).epu
: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.GPRD
: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.prev_day
: Previous day’s S&P 500 closing value, added for lag-based time series analysis.Feel free to use this dataset for academic, research, or personal projects.