📝 Description

This dataset contains over 400,000 macroeconomic events collected from global sources across more than 90 countries and regions, covering years 2020–2025. It mirrors professional economic calendars used by traders, economists, and analysts to track key economic indicators that move financial markets.

Each event includes its scheduled release time, geographical zone, currency, importance level, and actual, forecast, and previous values when available.

You can use this dataset for:

• 📈 Economic forecasting and sentiment analysis
• 💹 Financial market event-driven modeling
• 🧠 Machine learning applications on macroeconomic signals
• 🌍 Comparative studies of country-level indicators

📊 Dataset Structure

🌐 Coverage

• Zones: 90+ economies — including United States, Euro Zone, China, Japan, United Kingdom, India, Brazil, Australia, Türkiye, South Africa, and more.
• Currencies: USD, EUR, JPY, GBP, CNY, INR, and 50+ others.
• Time Period: ~2000 to 2025 (depending on data availability).
• Events Count: 409,234 records.

⚙️ Data Quality Notes

• Missing values in currency, importance, or actual columns occur mainly for minor or regional events.
• Times are reported as given in the source; some may represent local times.
• The dataset is cleaned and standardized for country and currency fields but can be further enriched with ISO country codes or UTC timestamps.

🧠 Example Use Cases

1. Market Volatility Forecasting: Use event importance and actual-vs-forecast deviations to predict short-term asset volatility.
2. Macroeconomic Trends: Track inflation or employment releases over time by country or region.
3. Event Sentiment Modeling: NLP on the event column for topic clustering (e.g., inflation vs. housing).
4. Calendar Effect Studies: Combine with asset price data (SPX, EURUSD, etc.) to measure event-driven reactions.

📦 File Info

• economic_calendar.csv

  • 409,234 rows
  • 10 columns
  • Size: ~31 MB

🏁 Tags

economics, macroeconomics, finance, forex, stock-market, forecasting, time-series, machine-learning, econometrics

🔗 Suggested License

If it’s scraped or aggregated from public calendars (like Investing.com), use: CC BY-NC-SA 4.0 — Attribution-NonCommercial-ShareAlike.

Economic calendar extracted from Investing.com (CSV) from 01-01-2015 to 31-12-2024 all countries

Columns

• Id of event
• Date (d-m-y)
• Hour of event
• Zone
• Currency
• Importance
• Event
• Actual
• Forecast (prediction of the market)
• Previous

The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

📅 Forex Factory Economic Calendar Dataset (2007-01-01 to 2025-04-07)

This dataset contains a comprehensive archive of macroeconomic calendar events sourced from Forex Factory, spanning from January 1, 2007 to April 7, 2025.Each row captures a specific event with detailed metadata including currency, event type, market impact level, reported values, and descriptive context.

  📦 Dataset Summary

Total timespan: 2007-01-01 → 2025-04-07
Format: CSV (UTF-8)
Timezone:… See the full description on the dataset page: https://huggingface.co/datasets/Ehsanrs2/Forex_Factory_Calendar.

Extracted economic calendar data from 23-01-2013 to 15-05-2023 from all countries.

Columns - date (d-m-y h:m:s) - title of the economic indicator - country from which data originate - indicator name - commentary on the change in value - actual value - previous value - forecast value for the next month - importance of the value

Africa Economic Calendar Dataset

  Dataset Description

This dataset contains 111,450 macroeconomic events from 18 African countries, spanning from 2020 to 2025. The dataset mirrors professional economic calendars used by traders, economists, and analysts to track key economic indicators that move financial markets. Each event includes its scheduled release time, geographical zone, currency, importance level, and actual, forecast, and previous values when available.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-economic-calendar-2020-2025.

content

This dataset records world economic events on a calendar basis. Date, time, country/zone, currency, event name, importance level, and actual/predicted/previous economic values (if available) are among the details that are included in each row, which represents a single event. Columns such as id, date, time, zone, currency, importance, event, actual, forecast, and prior are included in the dataset. These areas aid in monitoring market-moving announcements, national public events and holidays, and economic indicators.

context

Financial analysis, forecasting, and comprehending the impact of world events on markets and currencies may all be done with this dataset. These economic calendars are used by traders, economists, and data analysts to examine how significant announcements (such as interest rates, inflation figures, and holidays) affect market activity. Time-series forecasting models, market reaction studies, and EDA initiatives that investigate the connections between financial patterns and economic events can all benefit from its support.

Introduction

The global AI calendar market size is expected to be worth around USD 156.3 billion by 2034, up from USD 15.5 billion in 2024, growing at a CAGR of 26.0 % during the forecast period from 2025 to 2034. In 2024 North America held a dominant market position with more than 38.2 % share, equating to USD 5.92 billion in revenue. The rapid expansion reflects mounting enterprise and consumer adoption of AI-powered scheduling, optimisation and time-management solutions that leverage machine learning and cloud-based intelligence. The large growth potential stems from hybrid-work models, integration of calendars with productivity tools and rising demand for automation in meeting coordination.

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, 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 December 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.

US Tax Calendar

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

Introduction

Explore the archive of relevant economic information: relevant news on all indicators with explanations, data on past publications on the economy of the United States, Britain, Japan and other developed countries, volatility assessments and much more. For the construction of their forecast models, the use of in-depth training is optimal, with a learning model built on the basis of EU and Forex data. The economic calendar is an indispensable assistant for the trader.

ON THIS TOPIC Telegram : @Economic Calendar Investing Forex https://t.me/economic_calendar_forex_invest This channel will wake you up 5 minutes before important events of high volatility, as well as inform you of current data for monitoring from the investing economic calendar

Data set

The data set is created in the form of an CSV, Excel spreadsheet (two files 2011-2013, 2014-2019), which can be found at boot time. You can see the source of the data on the site https://www.investing.com/economic-calendar/

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1. column - Event date
2. column - Event time (time New York)
3. column - Country of the event
4. column - The degree of volatility (possible fluctuations in currency, indices, etc.) caused by this event
5. column - Description of the event
6. column - Evaluation of the event according to the actual data, which came out better than the forecast, worse or correspond to it
7. column - Data format (%, K x103, M x106, T x109)
8. column - Actual event data
9. column - Event forecast data
10. column - Previous data on this event (with comments if there were any interim changes).

Inspiration

1. Use the historical EU in conjunction with the Forex data (exchange rates, indices, metals, oil, stocks) to forecast subsequent Forex data in order to minimize investment risks (combine fundamental market analysis and technical).
2. Historical events of the EU used as a forecast of the subsequent (for example, the calculation of the probability of an increase in the rate of the Fed).
3. Investigate the impact of combinations of EC events on the degree of market volatility at different time periods.
4. To trace the main trends in the economies of the leading countries (for example, a decrease in the demand for unemployment benefits).
5. Use the EU calendar together with the news background archive for this time interval for a more accurate forecast.

Brazil ME: Exchange Rate: Current Calendar Year: Median data was reported at 5.900 USD/BRL in Mar 2025. This records a decrease from the previous number of 5.986 USD/BRL for Feb 2025. Brazil ME: Exchange Rate: Current Calendar Year: Median data is updated monthly, averaging 5.200 USD/BRL from Feb 2021 (Median) to Mar 2025, with 50 observations. The data reached an all-time high of 6.000 USD/BRL in Jan 2025 and a record low of 4.905 USD/BRL in Jul 2023. Brazil ME: Exchange Rate: Current Calendar Year: Median data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Global Database’s Brazil – Table BR.SD022: Market Expectation: Exchange Rate.

Moody's reported $89.74B in Market Capitalization this December of 2025, considering the latest stock price and the number of outstanding shares.Data for Moody's | MCO - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Overview with Chart & Report: Fed Labor Market Conditions Index is calculated monthly using 19 parameters. They include the unemployment rate, wages, number of job cuts, etc. The Fed applies it to comprehensively assess the labor

Brazil Market Expectation: Over Selic Rate: Annual Average: Current Calendar Year: Standard Deviation data was reported at 0.160 % pa in 28 Jun 2019. This records a decrease from the previous number of 0.170 % pa for 27 Jun 2019. Brazil Market Expectation: Over Selic Rate: Annual Average: Current Calendar Year: Standard Deviation data is updated daily, averaging 0.170 % pa from Jul 2002 (Median) to 28 Jun 2019, with 4244 observations. The data reached an all-time high of 1.800 % pa in 02 Jan 2003 and a record low of 0.000 % pa in 12 Dec 2018. Brazil Market Expectation: Over Selic Rate: Annual Average: Current Calendar Year: Standard Deviation data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA039: Market Expectation: Over Selic Rate: Annual Average. Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. The Over-Selic interest rate is set by the monetary authorities and has the role of signaling to economic agents the basic level of remuneration of federal securities. Its effective level is defined by the weighted average daily volume of operations backed by federal public short, medium and long-term securities at the present time. Such securities are issued by the Treasury or the Central Bank, negotiated and registered by the Special Settlement and Custody Service, Selic, in the form of repo operations. Notably, the Over-Selic interest rate has the function of guiding the other short-term interest rates of the economy, acting as a minimum limit.

Brazil Market Expectation: Over Selic Rate: Next Calendar Year: Median data was reported at 6.000 % pa in 28 Jun 2019. This records a decrease from the previous number of 6.500 % pa for 27 Jun 2019. Brazil Market Expectation: Over Selic Rate: Next Calendar Year: Median data is updated daily, averaging 11.750 % pa from Jan 2000 (Median) to 28 Jun 2019, with 4873 observations. The data reached an all-time high of 20.000 % pa in 30 Dec 2002 and a record low of 6.000 % pa in 28 Jun 2019. Brazil Market Expectation: Over Selic Rate: Next Calendar Year: Median data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA038: Market Expectation: Over Selic Rate. Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. The Over-Selic interest rate is set by the monetary authorities and has the role of signaling to economic agents the basic level of remuneration of federal securities. Its effective level is defined by the weighted average daily volume of operations backed by federal public short, medium and long-term securities at the present time. Such securities are issued by the Treasury or the Central Bank, negotiated and registered by the Special Settlement and Custody Service, Selic, in the form of repo operations. Notably, the Over-Selic interest rate has the function of guiding the other short-term interest rates of the economy, acting as a minimum limit.

Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Current Calendar Year data was reported at 3.330 PEN/USD in Oct 2018. This records an increase from the previous number of 3.300 PEN/USD for Sep 2018. Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Current Calendar Year data is updated monthly, averaging 3.260 PEN/USD from Jan 1999 (Median) to Oct 2018, with 231 observations. The data reached an all-time high of 3.780 PEN/USD in Jan 2000 and a record low of 2.500 PEN/USD in Feb 2013. Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Current Calendar Year data remains active status in CEIC and is reported by Central Reserve Bank of Peru. The data is categorized under Global Database’s Peru – Table PE.M010: Foreign Exchange Rate: Forecast: Central Reserve Bank of Peru.

Brazil ME: Exchange Rate: Current Calendar Year: Std Deviation data was reported at 0.168 USD/BRL in Mar 2025. This records a decrease from the previous number of 0.223 USD/BRL for Feb 2025. Brazil ME: Exchange Rate: Current Calendar Year: Std Deviation data is updated monthly, averaging 0.177 USD/BRL from Feb 2021 (Median) to Mar 2025, with 50 observations. The data reached an all-time high of 0.322 USD/BRL in Oct 2021 and a record low of 0.080 USD/BRL in Nov 2023. Brazil ME: Exchange Rate: Current Calendar Year: Std Deviation data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Global Database’s Brazil – Table BR.SD022: Market Expectation: Exchange Rate.

Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Next Calendar Year: Standard Deviation data was reported at 0.190 % in Jun 2019. This records an increase from the previous number of 0.150 % for May 2019. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Next Calendar Year: Standard Deviation data is updated monthly, averaging 0.405 % from May 2001 (Median) to Jun 2019, with 218 observations. The data reached an all-time high of 2.870 % in Nov 2002 and a record low of 0.100 % in Oct 2018. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Next Calendar Year: Standard Deviation data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SB017: Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15). Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Measures the variation of the costs of the expenses, as described in the IPCA, in the approximate period from the 15th of a month to the 15th of the subsequent month.

Brazil Market Expectation: GDP: YoY: Next Calendar Year: Standard Deviation data was reported at 0.420 % in 28 Jun 2019. This stayed constant from the previous number of 0.420 % for 27 Jun 2019. Brazil Market Expectation: GDP: YoY: Next Calendar Year: Standard Deviation data is updated daily, averaging 0.490 % from Jul 1999 (Median) to 28 Jun 2019, with 5010 observations. The data reached an all-time high of 1.410 % in 11 Mar 2010 and a record low of 0.240 % in 09 May 2007. Brazil Market Expectation: GDP: YoY: Next Calendar Year: Standard Deviation data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA001: Market Expectation: Gross Domestic Product: Percentage Change. Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Total GDP is the sum of all the wealth produced by a country in a given time span, usually one year. Total GDP is expressed in terms of the year analyzed. The total GDP is projected at market Prices.