From Employment to Stocks and Sectors
A considerable amount of focus is being placed on the potential impact that AI could have on the future of the white-collar employment landscape. From writing code to writing reports, jobs that are the preserve of a very narrow definition of “intellect” are potentially under severe threat. This is because AI now offers the possibilities of doing these tasks faster, doing them as well as a human counterpart could, and possibly better (in that there is the potential for less error).
There is the prospect that this will become an economic watershed moment, but that would not be an uncommon scenario from an economic historical point of view. There have been many such similar moments of technological advance in the past that resulted in a reordering of the types of human occupation.
This shift opens up many possibilities for investors to participate in and benefit from the AI economy. Consider, for example, the recent surge in Nvidia’s share price due to its higher-than-expected Q2 forecast because of a surge in demand for its AI chips.
But in spite of such a supply/demand opportunity, is it really just more of a same-old/same-old for the long-term investor rather than an age of many new opportunities to tackle investment challenges from new perspectives?
Long-term investors have seen the leading US companies, as measured by market capitalization, change in name and change in sector over the decades, so it is easy to understand the “Big Oil” to “Big Tech” to “Big AI” transition. For those with a blended US equity markets exposure—which encompasses almost all investors—the AI revolution will, for the typical investor, most likely simply be reflected in weighting adjustments to sector allocations.
For the sophisticated investors, however, the AI moment, if properly identified and acted upon, holds a whole other order of opportunity. This is not in the realm of faster, same or better than, human carried out tasks, but rather it is in the area of different.
AI in the task replacement field needs sameness, not difference. AI written reports, code or whatever will tend towards replication. Machine writing begets machine reading, begets similarity in style and structure, and a standardization of sorts.
Activating AI for Active Portfolio Management
Active money management, however, is a whole other field. It is an area where difference is edge and AI has the potential to bring a whole lot of untapped edge.
At Plotinus we know this from firsthand experience. Our journey building and using AI to enhance the accuracy of trade decision-making has been an educational one. For starters, unlike the rules of language or programming or accounting, the financial markets are—by definition—in flux. Data is fluid not fixed. It is a field of interpretation and conviction, not certainties. This dynamic information gives scope for a well-designed AI system to create interpretations off of changing data that are different. They are, in a sense, non-human interpretations. This is not that the “machine” is better at identifying patterns that a human observer may miss, like what we see with some AI deployed in medical analysis such as interpreting radiology scan images. Rather, it is that the perspective from which the analysis of financial data takes place is not the same as how we as the human observer would view it and thus seek to interpret it.
The skill of the portfolio managers who are today deploying AI is in seeing how these different machine-based perspectives on the market that they produce can be applied in investment strategies that use this differential and convert it into edge, providing investors with what is hopefully a long-term advantage.
The key for investors looking to now include AI-based investment strategies within their total portfolios is to dialogue with these money managers to determine, in the course of due diligence vetting, which of the managers can convey a sensible beyond-the-numbers explanation of their investment process that integrates the benefits of AI—as they are applying it to analytics and investment decision making—for a truly alternative investment. ■
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