Machine learning is another DRTI pillar. ML, a kind of artificial intelligence, allows advanced algorithms to evaluate enormous data sets to generate predictions based on predefined goals. Instead of exactly following human-coded instructions, these algorithms self-adjust via trial and error to create increasingly accurate prescriptions as more data is received.
The huge potential of AI and Machine Learning in investing strategies is in allowing far higher volumes and types of data to be used to guide investment choices, as well as potentially enhancing the interpretation of that data into investment evaluations.1
Early adopters are making considerable investments, and new product categories are emerging to promote alternate data sources, tools, and skill in analyzing it utilizing formerly innovative Machine Learning approaches.2
2 (Mullainathan, Sendhil and Jann Spiess. 2017. “Machine Learning: An Applied Econometric Approach.” Journal of Economic Perspectives 31 (2): 87–106).