The main stock market index of United States, the US500, rose to 6718 points on October 3, 2025, gaining 0.04% from the previous session. Over the past month, the index has climbed 3.31% and is up 16.80% 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 October of 2025.

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

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)

Sources

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.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.

In 2023, the leading equity index futures and options contract traded worldwide based on volume was Bank Nifty Index Options, traded on the National Stock Exchange of India. Over the year a total of ** billion Bank Nifty Index Options contracts were traded - over ** million more than second-placed CNX Nifty Index Options, also traded on the National Stock Exchange of India.

Import Volume Index data was reported at 130.173 2015=100 in 2021. This records an increase from the previous number of 118.805 2015=100 for 2020. Import Volume Index data is updated yearly, averaging 95.285 2015=100 from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 130.173 2015=100 in 2021 and a record low of 51.203 2015=100 in 2000. Import Volume Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Croatia – Table HR.World Bank.WDI: Trade Index. Import volume indexes are derived from UNCTAD's volume index series and are the ratio of the import value indexes to the corresponding unit value indexes. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, international and national sources, and UNCTAD secretariat estimates and calculates unit value indexes at the country level using the current year’s trade values as weights. For economies for which UNCTAD does not publish data, the import volume indexes (lines 73) in the IMF's International Financial Statistics are used.;United Nations Conference on Trade and Development, Handbook of Statistics and data files, and International Monetary Fund, International Financial Statistics.;;

The Trade Sentiment Index (TSI) dataset provides a real-time measure of how global trade narratives, tariff announcements, and geopolitical developments drive market sentiment across asset classes. Built using advanced natural language processing, the TSI ingests headlines from thousands of global sources, scoring them by tone, polarity, volume, and intensity. By quantifying narrative flows, the TSI offers investors a forward-looking lens on volatility at a time when traditional economic indicators often lag. The dataset captures how sentiment shocks around tariffs and trade align with price action in equities, commodities, FX, and rates, enabling systematic traders, portfolio managers, and strategists to: Detect leading indicators of cross-asset volatility. Anticipate market rotations in response to tariff rhetoric and trade negotiations. Stress test portfolios against geopolitical and trade-driven shocks. Enhance long-term allocation strategies with a sentiment-aware overlay. Key findings from recent analysis show: S&P 500 demonstrates the strongest correlation with trade sentiment, providing a useful proxy for global equity risk appetite. Copper has emerged as a geopolitical barometer, reacting sharply to tariff-driven disruptions. Gold, USD, and Treasuries show fragmented safe-haven behaviour, responding selectively to trade headlines. The TSI is available via API for seamless integration into trading, research, and risk workflows. It empowers investors to anticipate macro dislocations, tactical shifts, and regime changes in today’s sentiment-led markets.

Taiwan TWSE: Equity Market Index: Trading & Consumers' Goods data was reported at 265.650 31Dec1994=100 in Oct 2018. This records a decrease from the previous number of 276.610 31Dec1994=100 for Sep 2018. Taiwan TWSE: Equity Market Index: Trading & Consumers' Goods data is updated monthly, averaging 115.695 31Dec1994=100 from Jan 1995 (Median) to Oct 2018, with 286 observations. The data reached an all-time high of 276.680 31Dec1994=100 in Jun 2018 and a record low of 49.070 31Dec1994=100 in Apr 2003. Taiwan TWSE: Equity Market Index: Trading & Consumers' Goods data remains active status in CEIC and is reported by Taiwan Stock Exchange Corporation. The data is categorized under Global Database’s Taiwan – Table TW.Z001: Taiwan Stock Exchange (TWSE): Indices.

Graph and download economic data for Trade Weighted U.S. Dollar Index: Other Important Trading Partners, Goods (DISCONTINUED) (TWEXO) from 1995-01-04 to 2020-01-01 about trade-weighted, trade, exchange rate, currency, goods, rate, indexes, and USA.

Net Barter Terms of Trade Index data was reported at 99.930 2015=100 in 2021. This records an increase from the previous number of 99.062 2015=100 for 2020. Net Barter Terms of Trade Index data is updated yearly, averaging 100.967 2015=100 from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 108.386 2015=100 in 2001 and a record low of 97.159 2015=100 in 2018. Net Barter Terms of Trade Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank.WDI: Trade Index. Net barter terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes, measured relative to the base year 2000. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD's estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, international and national sources, and UNCTAD secretariat estimates and calculates unit value indexes at the country level using the current year's trade values as weights.;United Nations Conference on Trade and Development, Handbook of Statistics and data files, and International Monetary Fund, International Financial Statistics.;;

The trade-weighted index (TWI), also known as the real broad index, measures the strength of the US dollar relative to the currencies of the nation's trading partners. Weightings are determined by the share of trade with each country, with the five largest allocated to the Euro, Canadian dollar, Chinese yuan, Japanese yen and Mexican peso. These five currencies account for over two-thirds of the TWI. The data for this report is price adjusted (i.e. real) and sourced from the Economic Research Division of the Federal Reserve. Figures are based to an index value of 100 at January 2006.

Baltic Dry fell to 1,909 Index Points on October 2, 2025, down 3.59% from the previous day. Over the past month, Baltic Dry's price has fallen 1.60%, and is down 1.65% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Baltic Exchange Dry Index - values, historical data, forecasts and news - updated on October of 2025.

United States Net Barter Terms of Trade Index data was reported at 104.655 2015=100 in 2021. This records an increase from the previous number of 100.000 2015=100 for 2020. United States Net Barter Terms of Trade Index data is updated yearly, averaging 100.042 2015=100 from Dec 1980 (Median) to 2021, with 42 observations. The data reached an all-time high of 105.128 2015=100 in 1995 and a record low of 91.765 2015=100 in 1985. United States Net Barter Terms of Trade Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Trade Index. Net barter terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes, measured relative to the base year 2000. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD's estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, international and national sources, and UNCTAD secretariat estimates and calculates unit value indexes at the country level using the current year's trade values as weights.;United Nations Conference on Trade and Development, Handbook of Statistics and data files, and International Monetary Fund, International Financial Statistics.;;

At the end of February 2025, the DAX index reached ********* points, marking its highest level since January 2015. Moreover, this also reflected a strong recovery from the global coronavirus (COVID-19) pandemic, having risen from ******** points at the end of March 2020 and surpassing its pre-pandemic level of approximately ********* points at the end of December 2019. Origin and composition of the DAX Index The DAX (Deutscher Aktienindex) is the most important German stock index, showing the value trends of the 40 largest companies by market capitalization listed on the Frankfurt stock exchange. The DAX index was introduced on July 1, 1988 and is a continuation of the Börsen-Zeitung Index, established in 1959. The count among their number some of the most recognizable companies in the world, such as carmakers Volkswagen and Daimler, sportswear brand adidas, and industrial giants Siemens and BASF. After the DAX, the 50 next-largest German companies are included in the midcap MDAX index, while the 70 next-largest small and medium-sized German companies (ranked from 91 to 160) are included in the SDAX index. The Frankfurt Stock Exchange All the companies included in the DAX family of indices are traded on the Frankfurt Stock Exchange. Dating back to 1585, the Frankfurt Stock Exchange is considered to be the oldest exchange in the world. It is the twelfth largest stock exchange in the world in terms of market capitalization, and accounts for around ** percent of all equity trading in Germany. Two main trading venues comprise the Frankfurt Stock Exchange: the Börse Frankfurt is a traditional trading floor; while the Xetra is an electronic trading system which accounts for the vast majority of trading volume on Frankfurt Stock Exchange. As of December 2023, the total market capitalization of all companies listed on the Frankfurt Stock Exchange was around *** trillion euros.

United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data was reported at 168.237 Jan1997=100 in Nov 2018. This records an increase from the previous number of 166.528 Jan1997=100 for Oct 2018. United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data is updated monthly, averaging 96.825 Jan1997=100 from Jan 1973 (Median) to Nov 2018, with 551 observations. The data reached an all-time high of 168.237 Jan1997=100 in Nov 2018 and a record low of 1.998 Jan1997=100 in Jul 1973. United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.M016: US Dollar Trade Weighted Index.

The trade complementarity index indicates to what extent the export profile of the reporter matches, or complements, the import profile of the partner. A high index may indicate that two countries would stand to gain from increased trade, and may be particularly useful in evaluating prospective bilateral or regional trade agreements Note: This dataset uses mirrored data instead of country reported data.

Graph and download economic data for Economic Policy Uncertainty Index: Categorical Index: Trade policy (EPUTRADE) from Jan 1985 to Aug 2025 about uncertainty, trade, World, and indexes.

Graph and download economic data for Chain-Type Quantity Index for Real GDP: Wholesale Trade (42) in Iowa (IAWHOLEQQGSP) from Q1 2005 to Q1 2025 about quantity index, IA, wholesale, trade, private industries, GSP, private, industry, GDP, and USA.

Japan's main stock market index, the JP225, rose to 45770 points on October 3, 2025, gaining 1.85% from the previous session. Over the past month, the index has climbed 7.49% and is up 18.46% 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 October of 2025.

Graph and download economic data for Index of Trade and Industrial Activity for United States (M1205AUSM156SNBR) from Jan 1879 to Dec 1930 about trade, industry, indexes, and USA.

Bangladesh BD: Net Barter Terms of Trade Index data was reported at 68.332 2000=100 in 2020. This records an increase from the previous number of 65.803 2000=100 for 2019. Bangladesh BD: Net Barter Terms of Trade Index data is updated yearly, averaging 103.596 2000=100 from Dec 1980 (Median) to 2020, with 41 observations. The data reached an all-time high of 162.264 2000=100 in 1985 and a record low of 57.575 2000=100 in 2011. Bangladesh BD: Net Barter Terms of Trade Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Trade Index. Net barter terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes, measured relative to the base year 2000. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD's estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, international and national sources, and UNCTAD secretariat estimates and calculates unit value indexes at the country level using the current year's trade values as weights.;United Nations Conference on Trade and Development, Handbook of Statistics and data files, and International Monetary Fund, International Financial Statistics.;;

In April 2025, the China Maritime Silk Road Trade Index (STI) showed that the import and export trade indices to countries along the 'Belt and Road' project were ****** and ****** points, respectively. The STI 'Belt and Road' export index increased by more than *** percent over the previous month, while the STI 'Belt and Road' import index declined by almost ** percent over the previous month and by almost *** percent year-on-year.