SWOT your AI

If the recent market action has left you swinging, you should know we are living interesting times. The January performance that went by was the best U.S. market performance since 1987 [1]. The quarter that passed was the best since 2009 [2] and the recession we might or might not have is the unpredictable future. Between the two managers, the active and passive, the only thing constant was the swing. The former came with a performance fee and the option of extreme luck, i.e. you sold on October’18 top and bought at December’18 low. Congratulations! your active manager deserves the performance fee [3] for 2018. The latter is nearing zero fees and is indifferent to the swing or your swinging moods. He is willing to pay you for the swing. Where does this leave you; happier or riskier? It does not matter if you feel happier (markets recovered) and not riskier as AI or new tech is not there yet to make you feel confident about a bot managing your money or risk. The bot could flare up (large drawdown) before it delivers.

AI should be able to understand risk, understand human fallibility, understand the difference between robust behavior and fleeting patterns (garbage in garbage out [4]) before it can engender comfort. Where does AI for investment management stand today?  A Strength-Weakness-Opportunity-Threat analysis of AI vs. existing solutions brings out the key differentiators. AI should seek robust statistical behavior. AI should be performance attributed systematically (validated) if it has to overcome its weakness emanating from lack of track record. AI creates a diversification opportunity. Overuse of AI is the biggest threat; if it’s transparent.

Performance Returns for AlphaBots vs. Benchmarks (to end of March 2019);