Artificial intelligence is moving at a rapid pace and will soon be able to identify why an event occurred - this has profound implications for how we invest
Artificial intelligence's potential to help investors and traders was one of the most hotly debated topics at the recent Morningstar Investment Conference in Chicago.
BlackRock managing director and panellist Kevin Franklin kicked off proceedings with a quick Google search on the question, what is AI? The answer given by Google? "When a machine achieves the level of an intelligence of a human, then you can call it AI."
While AI is not quite there yet, speakers were excited about AI's future potential to help investors and professionals. One example is the ability of AI to perform "word mining" through text data sets, like earnings call transcripts.
Today, AI is capable of reading through an earnings call and learning and differentiating what is "bullish" versus what is "bearish". It appears that knowledge grows exponentially over time. Machines can now identify what word patterns may or may not lead analysts to make rating upgrades or downgrades.
The next frontier is what some experts call "strong AI", so that artificial intelligence not only extracts patterns in data but can also be creative. Strong AI, in theory, should be able to ask, fundamentally, "why did this happen?" and draw conclusions.
Another example of AI helping investing is in trading. As companies seek to build and expand their competitive edge they will be able to use AI to interpret massive amounts of trading data for every security in the world. With this development, firms can understand who bought and who sold which security. The advantage of this development, for example, allows firms' trading strategies to move away from crowded positions in the marketplace.
Computers Have Their Limits
Morningstar columnist Jon Rekenthaler looked at the use of AI in a recent article about chess and how computers learn.
"Hedge funds have long used artificial intelligence, with their short-term trades. However, neither they nor mutual funds have used machine learning to such an extent for their intermediate- to long-term trades. The vast majority of active decisions continue to be made either by humans, or by programs that obey human instructions."
And Rekenthaler is cautious about how far AI can fully replace human expertise in the financial markets.
"The artificial intelligence program cannot learn by playing itself – at least, not to the extent that it did when teaching itself chess. With a constrained, rules-based contest such as chess, a computer can glean as much insight from a hypothetical match, played against itself, as it can from evaluating an actual contest.
"Not so for the financial markets. It is difficult for a computer program to postulate how all other market participants might behave, so that it can devise a successful counter-strategy."
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