📝 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 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

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.

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.

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.

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.

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.

United Kingdom's main stock market index, the GB100, fell to 9690 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has declined 0.12%, though it remains 15.91% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on December of 2025.

Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Next Calendar Year data was reported at 3.350 PEN/USD in Nov 2018. This stayed constant from the previous number of 3.350 PEN/USD for Oct 2018. Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Next Calendar Year data is updated monthly, averaging 3.300 PEN/USD from Jul 1999 (Median) to Nov 2018, with 224 observations. The data reached an all-time high of 3.880 PEN/USD in Jun 2000 and a record low of 2.450 PEN/USD in Feb 2013. Peru BCRP Forecast: Exchange Rate against US$: Financial Entities: Next 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.

Total-Other-Finance-Cost Time Series for MicroStrategy Incorporated. Strategy Inc, together with its subsidiaries, operates as a bitcoin treasury company in the United States, Europe, the Middle East, Africa, and internationally. The company offers investors varying degrees of economic exposure to Bitcoin by offering a range of securities, including equity and fixed income instruments. It also provides AI-powered enterprise analytics software, including Strategy One, which provides non-technical users with the ability to directly access novel and actionable insights for decision-making; and Strategy Mosaic, a universal intelligence layer that offers enterprises with consistent definitions and governance across data sources, regardless of where that data resides or which tools access it. The company was formerly known as MicroStrategy Incorporated and changed its name to Strategy Inc in August 2025. The company was incorporated in 1989 and is headquartered in Tysons Corner, Virginia.

Financial-Leverage-Ratio Time Series for News Corp B. News Corporation, a media and information services company, creates and distributes authoritative and engaging content, and other products and services for consumers and businesses. It operates through five segments: Digital Real Estate Services, Dow Jones, Book Publishing, News Media, and Other. The company distributes content and data products through various media channels, such as newspapers, newswires, websites, mobile apps, newsletters, magazines, proprietary databases, live journalism, video, and podcasts under the MarketWatch, The Wall Street Journal, Barron's, Investor's Business Daily, Factiva, Dow Jones Risk & Compliance, Dow Jones Newswires, and Dow Jones Energy brands. It also owns and operates Monday to Friday, Saturday and Sunday, weekly, and bi-weekly newspapers comprising The Australian, The Weekend Australian, The Daily Telegraph, The Sunday Telegraph, Herald Sun, Sunday Herald Sun, The Courier Mail, The Sunday Mail, The Advertiser, Sunday Mail, The Sun, The Sun on Sunday, The Times, The Sunday Times, and New York Post, as well as digital mastheads and other websites. In addition, the company publishes general fiction, nonfiction, children's, and religious books; and operates Storyful, a social media content agency, as well as sports radio network and news channels. Further, it offers property and property-related advertising and services on its websites and mobile applications; digital real estate services; and financial services. The company has operations in the United States, Canada, Europe, Australasia, and internationally. News Corporation was incorporated in 2012 and is headquartered in New York, New York.

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

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

Retained-Earnings Time Series for Ally Financial Inc. Ally Financial Inc., a digital financial-services company, provides various digital financial products and services in the United States, Canada, and Bermuda. The company operates through Automotive Finance Operations, Insurance Operations, Corporate Finance Operations, and Corporate and Other segments. It offers automotive financing services, including providing retail installment sales contracts, loans and operating leases, term loans to dealers, financing dealer floorplans and other lines of credit to dealers, warehouse lines to automotive retailers, and fleet financing to consumers, automotive dealers and retailers, companies, and municipalities; and financing services to companies and municipalities for the purchase or lease of vehicles, and vehicle-remarketing services. The company also provides consumer finance protection and insurance products through the automotive dealer channel, and commercial insurance products directly to dealers; VSCs, VMCs, and GAP products; and underwrite select commercial insurance coverages, which primarily insure dealers' vehicle inventory. In addition, it provides senior secured asset-based and leveraged cash flow loans to middle-market companies; leveraged loans; commercial real estate product to serve companies in the nursing facilities, senior housing, and medical office buildings; and treasury activities, such as management of the cash and corporate investment securities and loan portfolios, short- and long-term debt, retail and brokered deposit liabilities, derivative instruments, original issue discount, and equity investments. Further, the company offers commercial banking products and services; and securities brokerage and investment advisory services. The company was formerly known as GMAC Inc. and changed its name to Ally Financial Inc. in May 2010. Ally Financial Inc. was founded in 1919 and is based in Detroit, Michigan.

Common-Stock Time Series for Hoist Finance AB. Hoist Finance AB (publ), a credit market company, engages in the loan acquisition and management operations in Europe. It operates through Unsecured and Secured segments. The company purchases performing and non-performing loans from its partners, international banks, and financial institutions. It also offers debt restructuring solutions. In addition, it provides savings, current, and fixed-term deposit account. The company was formerly known as Hoist International AB (publ) and changed its name to Hoist Finance AB (publ) in January 2015. Hoist Finance AB (publ) was incorporated in 1915 and is headquartered in Stockholm, Sweden.

Stock Price Time Series for Trust Finance Indonesia Tbk. PT Trust Finance Indonesia Tbk provides financing services in Indonesia. The company provides finances to passenger and commercial vehicles, as well as heavy equipment, such as excavators, bulldozers, and others. It offers services through agents and distributors. The company was formerly known as PT KIA Asia Finance and changed its name to PT Trust Finance Indonesia Tbk in February 2002. PT Trust Finance Indonesia Tbk was founded in 1990 and is headquartered in Jakarta, Indonesia.

Total-Other-Finance-Cost Time Series for Xgd Inc. XGD Inc., together with its subsidiaries, researches, develops, manufactures, sells, and services payment terminals in China and internationally. The company provides scene digital services, electronic payment products and audit services in payment terminals. It also offers BPO services that includes developing internet marketing, commercial debt management, software development, and technical consulting. XGD Inc. was founded in 2001 and is headquartered in Shenzhen, China.

Net-Income-From-Continuing-Operations Time Series for Anhui Xinli Finance Co Ltd. Anhui Xinli Finance Co., Ltd. provides various financial products and services in China. The company offers financial leasing, small loans, financing guarantees, insurance, and pawn services, as well as software and information technology and supply chain services. The company was formerly known as Anhui Chaodong Cement Co., Ltd. in March 2016. Anhui Xinli Finance Co., Ltd. was founded in 1999 and is based in Hefei, China.

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

Total-Other-Finance-Cost Time Series for AUTO1 Group SE. AUTO1 Group SE, a technology company, operates a digital automotive platform for buying and selling used cars online in Germany, France, Italy, and internationally. The company operates in two segments, Merchant and Retail. It is involved in the operation of AUTO1.com platform for the sale of used cars to commercial dealers; Autohero.com for the sale of used cars to private customers; and wirkaufendeinauto.de, an online platform to sell used cars to AUTO1. The company was founded in 2012 and is headquartered in Berlin, Germany.