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Global X Funds launches E-commerce ETF tracking NLP-based Solactive Index


New York-based ETF provider Global X has launched the Global X E-commerce ETF (EBIZ), which tracks the Solactive E-commerce Index (SOLEBIZ), SOLEBIZ uses a proprietary algorithm to select its index components.

E-commerce is experiencing a genuine boom. In 2017, 2.73 billion online shoppers accounted for sales of over USD2.3 trillion. While the user base is expected to grow to 3.1 billion people globally in 2021, the E-retail revenues are projected to rise to USD4.88 trillion in 2021.
To give investors exposure to this exciting market, Solactive developed its Solactive E-commerce Index consisting of companies that either: operate E-commerce platforms that connect buyers and sellers of goods and services via online marketplaces; provide E-commerce software, analytics or services that facilitate the development and enhancement of E-commerce platforms; or primarily sell goods and services online and generate the majority of their overall revenues from online retail.
The Solactive E-commerce Index utilises Solactive’s proprietary Natural Language Processing (NLP) engine called ARTIS (Algorithmic Theme Identification System), to identify thematic exposures in companies using unconventional data sources. ARTIS analyses large volumes of company reports, financial news, as well as business descriptions and reveals relationships between keywords that describe a theme and companies that are active in this very field.
The release of the Global X E-commerce ETF marks the second launch of a Global X ETF utilising Solactive’s ARTIS technology. The first was the Global X Autonomous & Electric Vehicles ETF (DRIV), listed in March 2018.
Timo Pfeiffer, Head of Research at Solactive, says: “Undoubtedly, it is safe to say that E-commerce will further define our consumption habits, which are focusing largely on the immediate availability of goods. As an innovative index provider, it is our pursuit to not only find the obvious but also take on different directions and perspectives on how to identify new sources for valuable index concepts”.

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