The disparate and fragmented data landscape for ETFs places a premium on data aggregation solutions, for both ETFs and indices, which should be integrated, clean and technically robust. Industry standard identifiers should widen the user base and promote open architecture models where players can choose best of breed vendors without being artificially locked into suboptimal contracts. This also helps trading, risk and enterprise data management teams to consolidate data acquisition into a single feed and user interface solution.
ETF data needs to be delivered in a user friendly format, through feeds and solutions. Clients should be able to access snapshots of historical and current ETF data at any point in time. They should be able to retrieve both raw data for their own manipulation and a single enriched and normalised dataset of ETF issuers for ease of inputting and comparison.
ETFs can be analysed with standard portfolio optimisation software, with multiple open source packages available on the web as well as a huge variety of vendor solutions. The breadth of the ETF universe means that a huge library of data covering different asset classes, geographies, markets and instruments would be needed for comprehensive analysis of a very diverse ETF portfolio. At the same time, investors who are using ETFs to access a more narrowly defined range of investments, such as US equities, may find much simpler packages are adequate.
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