Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis reveals areas in the investment landscape where machines are already very active and those where machines are likely to make significant inroads in the next few years.
KahnemanD, TverskyA. On the psychology of prediction. Psychol Rev, 1973; 80:237–251.
5.
OdeanT, GervaisS. Learning to be overconfident. Rev Financ Stud, 2001; 14:1–27.
6.
OdeanT, BarberB. Online investors: do the slow die first?. Rev Financ Stud, 2002; 15:455–487.
7.
ShefrinH, StatmanM. The disposition to sell winners too early and ride losers too long: theory and evidence. J Financ, 1985; 40:777–790.
8.
FrazinniA, KabillerD, PedersenL. Buffet's alpha. NBER working paper 19681. Cambridge, MA: National Bureau of Economic Research, November2013. Available online at www.nber.org/papers/w19681
