📝 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.

This index monitors perpetual and annual calendar complications from Patek Philippe 5140/5327, VC Patrimony, AP Royal Oak, Lange Langematik, JLC Master Perpetual, and IWC Portuguese. It tracks appreciation for mechanical calendar computers displaying day, date, month, year, moon phases, and leap year cycles. Use this index as a key indicator for intellectual complication preference, mechanical computer fascination, and long-term calendar functionality desirability.

A data set of payments made to vendors in 2021. Checkbook level data. When analyzing this data be aware that the sum amount and voucher are unique amounts, the payment amount is the total of a check. A check often includes more than one voucher. As a result of the Red Flag Commission recommendations, Ordinance 970032 was passed by the City Council Jan. 23, 1997. This ordinance requires the city to publish a report every two weeks listing all city payments.

A dataset of public corporate filings (such as annual reports, quarterly reports, and ad-hoc disclosures) for baby calendar Inc. (7363), provided by FinancialReports.eu.

Advanced sales data for statistical analysis decomposing Patek Philippe perpetual calendar returns into systematic (beta) and idiosyncratic (alpha) components. Essential for hedge funds building factor models for luxury watch investments. Includes stress testing during financial crises and quantified liquidity premiums across different market conditions.

The aim of this paper was to analyze the relationship between Mondays and the profitability provided by Brazilian hedge funds. We used a data basis composed of 3,337 hedge funds, totaling 3,529,808 observations of daily data, during the period from January 2005 until September 2013. To test the hypothesis, we used regression with panel data and we inserted control variables in the model that the literature points out as relevant. The main results showed that the Monday effect also occurs in the hedge funds segment and this effect is intensified in periods of financial crisis. However, we show that the effect is not consistent across all sub-categories of hedge funds. The results were persistent for funds which don't have a redemption period, as well as for the control for the Ibovespa daily returns. The discussion was mainly based on Behavioral Finance Theory in seeking potential explanations for this anomaly.

Provide the local tax tax calendar of the Yilan County Government Finance and Taxation Bureau.

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

Capital One Financial reported $468.11B in Trade Creditors for its fiscal quarter ending in June of 2025. Data for Capital One Financial | COF - Trade Creditors including historical, tables and charts were last updated by Trading Economics this last December in 2025.

This index monitors ladies' watches with complications including Cartier Tank MC calendar/Rotonde moon phase, Chanel Premiere moon phase/J12 calendar, Omega Constellation annual calendar/De Ville moon phase, Patek Philippe Twenty~4 calendar/Calatrava ladies complications, JLC Reverso ladies complications, and VC Patrimony ladies calendar. It tracks the appetite for mechanical complexity, sophisticated functionality appreciation, and women's technical horological interest.

The CSV files contain S&P historical data and are meant to be used in the Hull Tactical - Market Prediction competition.

With this dataset, you can - align the competition's date_id with real dates and analyze the seasonality of the data (weekly, yearly) - analyze the influence of holidays - analyze how the forward returns of the competition have been preprocessed - analyze the correlation with external events - and so on...

There are two files: - sp-historical.csv: S&P index. The 8990 rows of this CSV file correspond to the 8990 rows of the training dataset of the Hull Tactical - Market Prediction competition. - spy-historical.csv: SPY ETF. The forward returns in this file match train.csv better, but the file starts only in February of 1993 so that its rows correspond to the last 8210 rows of the training dataset.

The forward returns in spy-historical.csv were calculated as spy['forward_returns'] = (spy['Close'].shift(-1) + spy['Dividend'].shift(-1)) / spy['Close'] - 1

Jersey City Introduced Budget at the Regular Council Meeting on February 13, 2020.Click here for PDFClick here for Excel fileClick here for Amendments

Intro Budget Calendar Year 2016 PDFPreview

Japan MOF Forecast: Public Debt: MI: Calendar Based Market Issuance data was reported at 134,200.000 JPY bn in 2018. This records a decrease from the previous number of 141,300.000 JPY bn for 2017. Japan MOF Forecast: Public Debt: MI: Calendar Based Market Issuance data is updated yearly, averaging 142,050.000 JPY bn from Mar 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 156,600.000 JPY bn in 2013 and a record low of 106,300.000 JPY bn in 2008. Japan MOF Forecast: Public Debt: MI: Calendar Based Market Issuance data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under Global Database’s Japan – Table JP.F032: Central Government Debt: Forecast: Ministry of Finance.

This dataset is best for an advanced seasonal analysis of wine markets with timing optimization and calendar effect quantification for systematic trading strategies. Provides hedge funds with systematic approach to wine market timing. Includes release calendar correlation, seasonal demand patterns, and optimal timing strategies. Essential for wine investment timing optimization.

Intro Municipal Budget Calendar Year 2018 PDFPreview

Total-Other-Finance-Cost Time Series for Spearhead Integrated Marketing. FS Development Investment Holdings provides marketing services in China. It offers content, private, and meta universe marketing services. The company was formerly known as Spearhead Integrated Marketing Communication Group. The company was founded in 2003 and is based in Beijing, China.

User Friendly Budget Intro Calendar Year 2016 PDFPreview

Total-Other-Finance-Cost Time Series for Fiskars Oyj Abp. Fiskars Oyj Abp manufactures and markets consumer products for indoor and outdoor living in Europe, the Americas, and the Asia Pacific. It operates through Vita, Fiskars, and Other segments. The company offers products for the tableware, drinkware, jewelry, interior products, gardening, watering, outdoor, scissors and creating, and cooking products. It also involved in the museums and cultural, real estate, and forest management activities. It offers its products under the Fiskars, Royal Copenhagen, Georg Jensen, Iittala, Wedgwood, Waterford, Gerber, Moomin Arabia, Arabia, Hackman, Roga"ka, Royal Albert, Royal Doulton, and Rörstrand brand name. Fiskars Oyj Abp was founded in 1649 and is headquartered in Espoo, Finland.

Financial-Leverage-Ratio Time Series for World Acceptance Corporation. World Acceptance Corporation engages in consumer finance business in the United States. The company offers short-term small installment loans, medium-term larger installment loans, related credit insurance, and ancillary products and services to individuals. It also provides income tax return preparation and electronic filing services; and automobile club memberships. The company serves individuals with limited access to other sources of consumer credit, such as banks, credit unions, other consumer finance businesses, and credit card lenders. World Acceptance Corporation was founded in 1962 and is headquartered in Greenville, South Carolina.