Vol. 17, No. 3, 2019
The use of “big” data, algorithms and machine learning is disrupting investment management. By carefully selecting domains where data is sparse and there is possibility of regime changes, a human investor can not only survive, but thrive in a world of investment machines. When data is sparse, Bayesian methods allow probability theory to be used as logic rather than an exercise in statistics and thus enable forward looking investors to anticipate and position for these regime shifts. By focusing on strategy instead of tactics, investing in volatile markets, and by joining forces with machines, human investors can excel in the investment world that will be increasingly dominated by algorithms and Machine learning.