Had you asked John Bogle, the pioneer of index investing, about the merits of smart beta funds, he would have dismissed them as “just one more way of trying to do better”.
In the same way, active fund managers continue to search for a magic formula that will give them superiority over the market and the collective insight of all other investors combined. As far as we know, no one has yet succeeded. Even Warren Buffett, the greatest investor of the modern age, has lagged the S&P 500 over the past decade.
Some such advanced AI operators are already active, but much like the alchemist of old, their activities are shrouded in mystery and secrecy. We don’t know how far they have moved beyond extreme quantitative analysis, and with what success. Computer-game algorithms, such as for chess, compute several moves in advance. In Go, players have an average of 200 available moves per turn. For a computer to weigh just the next two possible moves of both players, it would have to consider more than 320-billion possible combinations. Anticipating the next four moves would involve 512-quintillion combinations .
In October 2017, DeepMind introduced AlphaGo Zero, a version without any human data inputs at all and which learned simply by playing games against itself. It quickly surpassed the human level of play and defeated the previous version of AlphaGo by 100 games to 0. The financial markets are none of these things. They accommodate an unlimited number of participants. There are no rules or laws that govern price moves, or how markets should behave at every turn. All we have is theories, such as the capital asset pricing model or arbitrage pricing theory, that attempt to explain what the markets are doing.
Source: Financial Digest (financialdigest.net)
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