An active, factor-based strategy focuses on tapping into new sources of data, on identifying relevant information and how to intelligently combine such information. Within this context alternative data – texts, images, or audio files – is becoming more important for the investment process, and regarding additional analytical value. At the same time, comprehensive and swift analysis requires state-of-the-art technology and plenty of experience.
As the amount of data continues to proliferate progressively, understanding all information relevant to investments (and the associated cross-linking) has outpaced human capability. Increasingly, investment success is becoming a question of the ability to process these huge amounts of data. Many traditional asset managers thus use the keyword “artificial intelligence” as bait. However, asset management is still a long way from deploying a strong artificial intelligence capable of making its own superior investment decisions within the scope of an investment process.
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