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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:
| Column | Description |
|---|---|
| id | Unique identifier for each event |
| date | Date of the economic event (YYYY-MM-DD) |
| time | Time of release (local or UTC depending on source) |
| zone | Country or region associated with the event |
| currency | ISO 3-letter currency code (e.g., USD, EUR, JPY) |
| importance | Event impact level on markets: low / medium / high |
| event | Description or title of the event (e.g., “CPI YoY”, “GDP Growth Rate”) |
| actual | Reported actual value (if available) |
| forecast | Expected or forecasted value (if available) |
| previous | Previously reported value (if available) |
currency, importance, or actual columns occur mainly for minor or regional events.event column for topic clustering (e.g., inflation vs. housing).economic_calendar.csv
economics, macroeconomics, finance, forex, stock-market, forecasting, time-series, machine-learning, econometrics
If it’s scraped or aggregated from public calendars (like Investing.com), use: CC BY-NC-SA 4.0 — Attribution-NonCommercial-ShareAlike.
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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.
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This dataset contains 2000 daily stock market records including price movements, trading volume, market trends, indices, economic scores, and market sentiment information. It covers multiple sectors with a general category column and includes a target column for the next-day closing price. Additional text columns capture market sentiment and news tags for each record. The dataset is designed to provide comprehensive insights into stock market behavior and trends.
Number of Records: 2000
Number of Columns: 18
Column Descriptions:
Category – General text representing the sector or type of stock (e.g., Tech, Finance, Health).
Date – The calendar date of the stock record.
Open – The opening price of the stock on that day.
High – The highest price of the stock during the day.
Low – The lowest price of the stock during the day.
Close – The closing price of the stock on that day.
Volume – The total number of shares traded during the day.
SMA_10 – The 10-day simple moving average of the closing price, showing short-term trend.
EMA_10 – The 10-day exponential moving average of the closing price, giving more weight to recent prices.
Volatility – The standard deviation of the closing price over a 10-day window, representing price fluctuation.
Wavelet_Trend – Trend component of the closing price over a 10-day period.
Wavelet_Noise – Difference between the actual closing price and the trend component, capturing minor fluctuations.
Wavelet_HighFreq – Daily price changes in closing price, showing high-frequency movement.
General_Index – A numeric indicator representing general market performance.
Economic_Score – A numeric score representing overall economic factors impacting the stock.
Market_Sentiment – Text describing the sentiment of the market for that day (Positive, Neutral, Negative).
News_Tag – Text describing the main type of news impacting the stock on that day (e.g., Earnings, Merger).
Close_Next – The closing price of the stock for the next day, serving as the target variable.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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Japan's main stock market index, the JP225, rose to 49553 points on December 2, 2025, gaining 0.51% from the previous session. Over the past month, the index has declined 3.78%, though it remains 26.25% higher than a year ago, 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 December of 2025.
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The main stock market index of United States, the US500, rose to 6849 points on November 28, 2025, gaining 0.54% from the previous session. Over the past month, the index has declined 0.60%, though it remains 13.54% 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 November of 2025.
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Find detailed analysis in Market Research Intellect's Calendar Market Report, estimated at USD 70 billion in 2024 and forecasted to climb to USD 90 billion by 2033, reflecting a CAGR of 4.5%.Stay informed about adoption trends, evolving technologies, and key market participants.
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Calendar App Market size was valued at USD 5.71 Billion in 2024 and is projected to reach USD 16.37 Billion by 2032, growing at a CAGR of 10.4% during the forecast period 2026-2032.Global Calendar App Market DriversThe growth and development of the Calendar App Market is attributed to certain main market drivers. These factors have a big impact on how Calendar App are demanded and adopted in different sectors. Several of the major market forces are as follows:Enhanced Digitization and Connectivity: As people depend more and more on digital tools to manage their personal and work calendars, there is a need for calendar apps that are user-friendly, accessible, and compatible with a variety of devices.Growing Adoption of Smart Devices: The widespread use of calendar apps for on-the-go schedule management, which boosts productivity and convenience, is encouraged by the proliferation of smartphones, tablets, smartwatches, and other connected devices.Synchronization and Cross-Platform Integration: Users benefit from unified and synchronized schedules when calendar apps effortlessly integrate and synchronize across many platforms, such as email clients, task management tools, and cloud services. This is what makes these apps so popular.Personalization and Customization Features: Apps that accommodate user preferences by providing configurable features like color-coding, event classification, reminders, and several viewing options improve user experience and adoption.Collaborative and Sharing Capabilities: Professional and personal settings can benefit from the adoption of calendar apps that include collaboration tools that enable many users to share and sync calendars, arrange meetings, and plan events among teams or families.AI and Smart Scheduling: Tasks related to scheduling are streamlined, increasing productivity and time management, with the integration of artificial intelligence (AI) capabilities including predictive scheduling, smart suggestions, and automatic event organization.Productivity Gains: By providing a unified platform for organizing both events and activities, calendar apps that incorporate task management, to-do lists, notes, and goal-setting features help users be more productive.Remote Work and Flexibility: The COVID-19 epidemic and shifting work dynamics have led to a trend toward remote work and flexible scheduling, which has increased demand for efficient calendar apps that facilitate time management and remote collaboration.User Experience and Interface Design: Users looking for seamless experiences are drawn to calendar applications because of their intuitive user interfaces, user-friendly designs, and easy navigation.Growing Importance of Time Management: Calendar apps that provide tools for effective time allocation, prioritization, and goal setting are becoming more and more popular among users as attention on time management and work-life balance grows.
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This research tests the Adaptive Market Hypothesis (AMH) regarding calendar anomalies in the Baltic stock markets. Analysis of known calendar anomalies over time is carried out by using sub-sample GARCH (1,1) regression with Kruskal–Wallis statistics and rolling windows. Three calendar anomalies were confirmed in these markets: Friday, MoY (July and January), and ToM (turn-of-the-month). The Baltic stock markets demonstrated behavior supporting the AMH. It was found that the opportunity to earn abnormal returns on investment strategies based on Friday, July, and ToM effects disappeared during the financial crisis of 2007–9. The Friday and the ToM effects follow a more time-varying pattern, while the July effect is less so.
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The size of the Calendar App market was valued at USD XXX million in 2024 and is projected to reach USD XXX million by 2033, with an expected CAGR of XX% during the forecast period.
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Global Calendar market size 2021 was recorded $36393.7 Million whereas by the end of 2025 it will reach $43400.2 Million. According to the author, by 2033 Calendar market size will become $61719.4. Calendar market will be growing at a CAGR of 4.5% during 2025 to 2033.
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Get key insights on Market Research Intellect's Calendar App Market Report: valued at USD 1.45 billion in 2024, set to grow steadily to USD 4.2 billion by 2033, recording a CAGR of 15.2%.Examine opportunities driven by end-user demand, R&D progress, and competitive strategies.
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Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on December of 2025.
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The size of the Calendar Software market was valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2032, with an expected CAGR of XX% during the forecast period.
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India's main stock market index, the SENSEX, rose to 83952 points on October 17, 2025, gaining 0.58% from the previous session. Over the past month, the index has climbed 1.13% and is up 3.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on October of 2025.
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Check Market Research Intellect's Calendar Software Market Report, pegged at USD 5.6 billion in 2024 and projected to reach USD 11.5 billion by 2033, advancing with a CAGR of 8.6% (2026-2033).Explore factors such as rising applications, technological shifts, and industry leaders.
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The global calendar software market is projected to reach $236.7 billion by 2033, growing at a CAGR of 11.1% from 2025 to 2033. Key drivers of this growth include the increasing adoption of cloud-based and web-based calendar software, as well as the growing need for collaboration and scheduling tools in the workplace. Emerging trends such as the use of artificial intelligence (AI) and machine learning (ML) in calendar software are also contributing to the market's growth. The market is segmented by type (cloud-based and web-based) and application (large enterprises and SMEs). Among these segments, the cloud-based segment is expected to hold the largest market share during the forecast period, due to the benefits it offers, such as accessibility, scalability, and cost-effectiveness. The large enterprises segment is expected to be the largest application segment, as these organizations require robust and feature-rich calendar software solutions. Geographically, North America is expected to dominate the market, followed by Europe and Asia Pacific.
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Global Desk Calendar Market is segmented by Application (Office Supplies_ Organization_ Time Management_ Planning_ Stationery), Type (Wall Calendars (Often Compared)_ Desk Pads_ Desk Blotters_ Daily Planners_ Weekly Planners), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)
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Market Overview The global online calendar apps market is estimated to be valued at USD XXX million in 2025 and is projected to grow at a CAGR of XX% from 2025 to 2033. The growth of this market is attributed to the increasing adoption of cloud-based solutions, the need for effective time management, and the growing demand for collaboration and communication tools. Market Drivers, Trends, and Challenges Key drivers of the market include the increasing popularity of remote work, the proliferation of smartphones and tablets, and the growing importance of data privacy and security. Emerging trends in the market include the integration of artificial intelligence, the adoption of mobile apps, and the growing popularity of subscription-based models. However, challenges such as competition from incumbents, data security concerns, and the availability of open-source alternatives may hinder market growth.
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Index Time Series for NEXT NOTES Tokyo Stock Exchange Mothers. The frequency of the observation is daily. Moving average series are also typically included. NA
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License information was derived automatically
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:
| Column | Description |
|---|---|
| id | Unique identifier for each event |
| date | Date of the economic event (YYYY-MM-DD) |
| time | Time of release (local or UTC depending on source) |
| zone | Country or region associated with the event |
| currency | ISO 3-letter currency code (e.g., USD, EUR, JPY) |
| importance | Event impact level on markets: low / medium / high |
| event | Description or title of the event (e.g., “CPI YoY”, “GDP Growth Rate”) |
| actual | Reported actual value (if available) |
| forecast | Expected or forecasted value (if available) |
| previous | Previously reported value (if available) |
currency, importance, or actual columns occur mainly for minor or regional events.event column for topic clustering (e.g., inflation vs. housing).economic_calendar.csv
economics, macroeconomics, finance, forex, stock-market, forecasting, time-series, machine-learning, econometrics
If it’s scraped or aggregated from public calendars (like Investing.com), use: CC BY-NC-SA 4.0 — Attribution-NonCommercial-ShareAlike.