What is Dividend Data? Best Datasets & Databases for Dividend History Data
What is Dividend Data?
Dividend data refers to information related to the dividends paid by a company to its shareholders. It includes details such as the dividend amount, payment date, ex-dividend date, and dividend yield. This data is important for investors as it helps them assess the financial health and profitability of a company, and make informed decisions regarding their investment portfolios.
Examples of dividend data include the amount of dividends paid, the dates of dividend payments, and the dividend yield. Dividend data is used by investors and analysts to assess the financial health and performance of a company, make investment decisions, and calculate dividend income. In this page, you’ll find the best data sources for dividend data, dividend history data, historical dividend data, dividenddata, dividend database, and download dividend history.
Best Dividend Databases & Datasets
Here is our curated selection of top Dividend Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.
IvyDB Implied Dividend - Options Data, Options Data, Dividend Data and Trading Data
EDI Woodseer Dividend Forecasting Global (25k+ securities, 1000+ indices)
Woodseer Dividend Forecast Data
Anachart | Public Companies Dividend History | NASDAQ & NYSE | Over 35,000 Documented accessible Individual Dividends | 24 Years of History
Global ETF Data | ETF Dividends | Reference ETF data | ETF Holdings | 9K ETF
Woodseer ETF Data - ETF Data, Alternative Data, Derivatives Data, Dividend Data and Dividend Forecast
EDI Global Corporate Actions Data for Shares | Stocks | Equities | 60 Event Types incl. Dividends, Splits, Spin-offs and more | Historical Data avail.
Woodseer ETF Dividend Forecast Data
Historical Dividends API by Finnworlds
Global Corporate Actions Stock Data | Stock Reference Data | Dividends and Splits | 80K stocks
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Frequently Asked Questions
Where Can I Buy Dividend Data?
You can explore our data marketplace to find a variety of Dividend Data tailored to different use cases. Our verified providers offer a range of solutions, and you can contact them directly to discuss your specific needs.
How is the Quality of Dividend Data Maintained?
The quality of Dividend Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Dividend Data Updated?
The update frequency for Dividend Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Dividend Data Secure?
The security of Dividend Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Dividend Data Delivered?
Dividend Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Dividend Data.
How Much Does Dividend Data Cost?
The cost of Dividend Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Dividend Data for your needs.
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