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Goldbaum Aggregated Fund Portfolio and Basket Analytics for ETF/ETP/ETCs - Global Coverage

by Goldbaum
, .TXT, .JSON/.JSONLINES directly from our API UI or Data UI bespoke Data Services such as Data Cleansing ... In addition to our Data API, our service deliveries also include: downloadable files in .XLS, .CSV
Available for 249 countries
200K Financial security identification number (ISIN,Exchange Symbol, CUSIP, WKN, SEDOL)
2 years of historical data
100% End-of-day data released as exchanges and providers do (no lags)
Starts at
$100 / purchase
10% Datarade discount
Free sample available
20% revenue share
Instantly Purchasable Datasets
Sample of Goldbaum Datasets

Company and ETF ESG Screens for global companies by ESG Analytics

by ESG Analytics
Controversial Weapons Oil and Gas Nuclear Innovation and many others The company screening data ... The data set contains 25 indicators for 7,900 public companies across global geographies, including involvement
Available for 106 countries
8.5K Companies
Starts at
$1,500 / purchase
Free sample available
Instantly Purchasable Datasets
S&P 500 ESG exclusionary and inclusionary investment screens

RIMES ETF Multiple Basket Data

by RIMES Technologies
RIMES Managed Data Services support all forms of ETF activity by providing validated daily ETF composition ... Leveraging our award-winning Managed Data Services, RIMES normalizes, validates and enriches ETF data
Available for 249 countries
6.6K ETFs/ETPs
100% Customizable
Pricing available upon request
Free sample available

Woodseer ETF Dividend Forecast Data

by Woodseer Global
Bottom-up calculated ETF dividend forecast data for 700+ US listed optionable ETFs Working closely with ... Combining ULTUMUS’ ETF compositional data daily (including changing constituents, fees and cash balance
Available for 107 countries
700 US listed ETFs
5 years of historical data
Available Pricing:
Monthly License
Yearly License
10% Datarade discount
Free sample available
revenue share

Goldbaum EOD and Historical Data Analytics for ETF/ETP/ETCs - Global Coverage

by Goldbaum
, .TXT, .JSON/.JSONLINES directly from our API UI or Data UI bespoke Data Services such as Data Cleansing ... and Data Insights.
Available for 249 countries
100K Financial security identification number (Exchange Symbol, CUSIP, WKN, SEDOL)
25 years of historical data
100% End-of-day data released as exchanges and providers do (no lags)
Starts at
€20€18 / ISIN
10% Datarade discount
Free sample available
20% revenue share

RIMES Global ETF Data Management

by RIMES Technologies
RIMES ETF offering provides high-quality customizable ETF data directly from source in order to provide ... RIMES Managed Data Services support all forms of ETF activity by providing validated daily ETF composition
Available for 249 countries
6.6K +, ETFs/ETPs
100% Bespoke Format
Available Pricing:
Monthly License
Yearly License
Free sample available - Twelve Data profile banner
Twelve Data
Based in Singapore
Twelve Data
We take the financial market data of the highest quality, add convenient formats and tools, with all running in cloud infrastructure - this is the recipe for...
Requests daily
Global exchanges - Exchange Data International profile banner
Exchange Data International
Based in United Kingdom
Exchange Data International
With EDI you get high quality, affordable financial data customized to precisely fit your operational requirements.
Certified - Finage profile banner
Based in United Kingdom
Finage is a real-time stock, currency and cryptocurrency data provider company via API, WebSocket & Widgets. Easy, secure and affordable way to build financi...
Requests - ESG Analytics profile banner
ESG Analytics
Based in Canada
ESG Analytics
ESG Analytics uses alternative data to evaluate ESG dimensions for companies, countries and investment funds.
Speed - EPFR Global profile banner
EPFR Global
Based in USA
EPFR Global
EPFR’s Flows and Allocations data provides a unique view on investor and fund manager sentiment across global markets, helping buy and sell-side institutions...
25 years
Data sourced direct from
$50 Tr
Tracked AUM - Pynk profile banner
Based in United Kingdom
Pynk is a wealth management fintech with over 70,000 users. Users predict asset prices on our gamified platform at These user-generat...
Global Users
Weekly Total Predictions
Countries Presence

The Ultimate Guide to ETF Data 2021

Learn about etf data analytics, sources, and collection.

What is ETF Data?

ETF data (exchange traded funds data) is a sub-category of financial market data. ETF data refers to information on shares sold on an exchange. It is financial market data on securities with the combined features or characteristics and benefits of mutual funds, bonds and stocks. Exchange traded funds shares are traded like shares on the basis of demand and supply, and also represent an assembled portfolio, like mutual funds, so an ETF dataset represents all information on these securities.

How is ETF Data collected?

Since ETF data is related directly to financial market data, the means of data collection lie in the regular collection methods and processes used for finanical market data. An array of sources provide the information used to compile ETF data feeds. These sources include market research firms, securities exchanges, news aggregators, brokers, traders, online services and investors. These sources monitor the listings of securities and their performances, analyzing details such as trading indexes and prices. This is then compiled on daily basis and used to make portfolio decisions in choosing what securities to buy and invest in.

What are the attributes of ETF Data?

Exchange traded funds are traded like both day to day stocks and mutual funds. Because of these characteristics, exchange traded funds data must be made up of information on equity portfolios as well as bonds portfolios. ETF data must show an index tracking of a market commodity or pool of assets.
ETF data attributes can also refer to how popular market items are traded, for example the ease and speed of trade that stocks are associated with.

What is ETF Data used for?

ETF data is essential in the creation and optimization of portfolios. Portfolio optimization here involves the selection of exchange traded securities or products and combining them in such a way that they mature and yield profitable returns to investors. The data allows investors to understand and predict the performance of the exchange traded funds. Proper analysis of ETF data gives investors a range of market options consisting of bonds, stocks, currencies or commodities and affords them the opportunity to pick out the best options that are not just profitable, but also come with as low risks as possible.

How can a user assess the quality of ETF Data?

The basic process for assessing the quality of any sub-cateogry of financial market data applies here. Exchange traded funds data must possess the following characteristics to be deemed high quality:
Authenticity - ETF data must come from a trustworthy source. Check for ETF data provider reviews to verify that the information it contains is accurate.
Reliability - any intelligience provided by ETF data must be impartial and unbiased.
Accessibility - all information in ETF data must be straightforward, easy to access and primed for analytics.
Timeliness - ETF data must match the time of its usage, as market conditions change every second.
Relevance - ETF data must be fit for purpose and match its user’s intended use case.

How to find ETFs?

For investors, buying Exchange Traded Funds is considered a small and low-cost strategy to build an optimal portfolio. When finding ETFs, it is critical that investors follow the factors below:

• Level of assets - When looking to find a more viable selection of investment choice, an ETF is expected to have a bottom line level of assets, a common threshold being $10 million as the bare minimum.
• Trading activity - Trading activities is an important indicator of liquidity so much so that higher trading volume of an ETF, can be interpreted to mean higher liquidity - Underlying index or asset upon which the ETF is founded should be taken into account. As far as diversification is concerned, finding ETFs that are based on a wider scope rather than an obscure index.

Can you analyse ETF Data by holdings?

ETF data analysis by the depth of holdings is an important initiative that helps investors to have access to a list of securities with a mere purchase of a single share. They provide avenues for small time investors to gain access to a large, and well-diversified pool of assets. The example below shows that it is possible to analyse ETF data by holdings:

> ‘The FTSE/Xinhua China 25 Index Fund (FXI A-) has 54 individual holdings, while the SPDR S&P China ETF (GXC A) has about 356.’

From this data, an analysis can be drawn to show that more isn’t particularly better, but at times, it is advantageous to concentrate holdings in a small group of securities but the overall depth of exposure given can show a meaningful impact on an ETF’s risk/return profile.

How to carry out ETF analytics?

In the analysis of ETFs, it is critical that investors take into account the underlying indexes and classification benchmarks that are meant to determine the types of stocks that are more likely to be part of the ETF. Additionally, tracking down of the fund’s trading history in the given wide-ranging markets is important initiatives that can help investors assess how the fund performed. Carrying out ETFs analytics involves looking at charts for the ETFs of concern to determine their historical performance. For a well-seasoned investor, understanding ETFs charts is simple because they trade just the same way as stocks in most major exchange markets. While looking at ETFs historical data performance may not necessarily give full insight about the future changes, it still gives investors the opportunity to determine and decide the kind of ETFs they want to use.

What is an ETF screener?

An ETF screener is basically an internet-based or software program that assists its users to find and determine ETFs, a process that is accomplished upon setting of certain conditions in order to narrow down or churn out the search from all the ETFs currently available on the market. The process of using an ETF screener usually entails the investor inputting search queries that narrows down on the type of ETF. From this point, the investor then uses the ETF screener to display all the publicly traded ETFs that are further grouped either as large-cap stock, or a sub-category such as large-cap growth or large-cap value, further setting the screener to sort the funds data to smaller subsets.

What is an ETF holdings database?

An ETF is a type of security that involves a collection of securities, that usually tracks an underlying index, but they can also invest in any given industry sectors. ETFs can encompass various types of investments that range from stocks, commodities, bonds, or a combination of various investment types. The key feature of ETFs is that they are marketable securities, a factor that identifies them to have an associated price for them to be easily bought and sold. Therefore, an ETF holdings database refers to a system of information that stores data about ETFs trading activities on the security exchange markets. This database captures the ETF share price fluctuations, the types of investments that include stocks, commodities or bonds and the types of expense ratios associated with them. The ETF holding databases are made available by data commercial data providers where they are listed in such a way that consumers can buy ETF data, either through over-the-counter method or they can buy ETF data online while in a remote location.

How do ETFs make money?

ETFs consists of various types which are made available for people looking to invest for the purpose of generating income, speculation, price increases, and to hedge or partly offset risks in an investor’s portfolio. Types of ETFs used by investors for making money include:

• Bond ETFs that include government binds, corporate bonds, and state and local bonds.
• Industry ETFs that are designed to keep track of a certain industry such as technology and banking.
• Commodity ETFs that entails investing in commodities such as crude oil or gold.
• Currency ETFs that involve investing in foreign currencies.

What is ETF performance data?

Looking at historical ETF data may not tell an investor how the same ETFs are bound to perform in the future. However, looking at this historical data, while combined together with real-time ETFs data can give an investor some meaningful insights of how the ETF has performed in different market settings and conditions. Therefore, an ETF performance data refers to historical and real-time information that shows how a selected ETF has been performing in the market place. Information about the performance of ETFs is available as a commercial ETF dataset in the data marketplace which can be acquired by interested parties, investors, through purchase of ETF data, by means of ETF data subscription that can range from monthly to yearly. The cost of ETF data as provided for by data vendors is dependent on the quality attributes of the data such as completeness and accuracy as well as volume of the data that an investor is looking to buy.

Who are the best ETF Data providers?

Finding the right ETF Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular ETF Data providers that you might want to buy ETF Data from are Twelve Data, Exchange Data International, Finage, ESG Analytics, and EPFR Global.

Where can I buy ETF Data?

Data providers and vendors listed on Datarade sell ETF Data products and samples. Popular ETF Data products and datasets available on our platform are Goldbaum Aggregated Fund Portfolio and Basket Analytics for ETF/ETP/ETCs - Global Coverage by Goldbaum, Company and ETF ESG Screens for global companies by ESG Analytics by ESG Analytics, and Global Stock, ETF, and Index data by Twelve Data.

How can I get ETF Data?

You can get ETF Data via a range of delivery methods - the right one for you depends on your use case. For example, historical ETF Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time ETF Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to ETF Data?

ETF Data is similar to Short Interest Data, Stock Fundamental Data, Intraday Stock Data, Stock Price Data, and Corporate Actions Data. These data categories are commonly used for Portfolio Optimization.

What are the most common use cases for ETF Data?

The top use cases for ETF Data are Portfolio Optimization.

Translations for this page

Datos ETF (ES)