“What is alternative data in finance, what is its role, and how does it relate to data driven investing?” This was just one of the discussion questions posed to the three panelists during “The Role of Alternative Data in Finance” session. The moderator Megan Kelley from Fidelity Labs probed around the themes of proving the value of a given data set, what an ideal data set actually looks like, and the role of compliance as it relates to data for the finance world. This panel, including Shaivali Shah of Morgan Stanley Research, started by defining and discussing exactly what “data driven investing” is all about, which focuses on using data to produce “Alpha” (generating returns higher than a benchmark index, such as the S&P 500 for example).
One of the big themes that emerged from the panelists was regarding trust and the need for clean and accurate data. Matei Zatreanu from System2 noted that “At the end of the day you’re really solving for trust.” Pierce Crosby from StockTwits added that the whole concept of social data is inherently tricky – you need to trust the contributors to the data set, not solely the end provider you are working with.
Another large theme discussed was not only about the raw data itself, but the associated value that data ultimately provides. Matei went on to note that “At the end of the day these folks don’t care about the data, they just want the insights.” Pierce expanded further that if you can summarize statistics early on, it can go a long way towards getting people more comfortable.
The panel concluded with a discussion about key use cases and areas of opportunity: one that was unanimous was around the immense potential for collecting more and larger data sets around emerging markets.