As we discussed in our first piece, different markets around the world dance to their own unique beats. Understanding these nuances is crucial for any investor, as expecting these differences to even out in the long run may be misguided. They have their own ways and methods that appear entirely nonsensical outside their context, giving rise to distinct trading patterns, valuation ranges, and investment opportunities.
One example of these peculiarities is how financial year-end dates are labelled in different countries. For instance, a Japanese company with a financial year-end in March 2023 would refer to it as FY22 as per the locally accepted convention, while an Indian company with the same year-end date would call it FY23.
The U.S. equities market, in particular, stands out for its dramatic reactions to data releases and earnings reports. Each event becomes a spectacle, a phenomenon rarely witnessed elsewhere. Last week's market movements provided a prime example of this peculiarity. Tesla, despite missing earnings expectations, saw its stock price soar by double digits, while Meta, exceeding expectations, experienced a significant decline. Lest anyone wants to work on the Inefficient Market Hypothesis, there were results and performances in the same direction, too! Alphabet enjoyed a double-digit surge after beating estimates.
Frequent double-digit moves are not the only peculiarities in the market, which is extraordinarily stable top-down. Beyond price reactions, the nature and depth of analyst inquiries also vary considerably across borders. In the U.S., the practice of tech giants like Google, Microsoft, and Amazon offering cloud credits to clients in lieu of cash payments has hardly raised any eyebrows. These credits, rather than being treated as liabilities, are often recorded as investments, potentially at inflated valuations. Such a practice might have attracted far more scrutiny and demand for transparency in emerging markets.
Perhaps the numbers are small or trivial, but they may have explained minor differences in growth patterns of Meta (who has no such business) versus others. Absence from discussions on this is uniquely American, reflecting the U.S. market's distinct language.
Meta is clearly in a penalty box, or there should have been more reaction to its GenAI introductions in its apps for implications on the more favored giants’ search and Chatboxes. Unlike some other peculiarities, the ones arising from the LLM pervasiveness cannot be put off further. Just like the sensational acceleration in Robotics, which the latest MIT Journal had to acknowledge with the cover article titled “Is robotics about to have its own ChatGPT moment?” We are sure to talk about that repeatedly in the coming posts as this has been our most expected innovation theme from the time we started writing these posts and explaining why the era of AI is not about Chatboxes or why Tech ≠AI ≠ Innovation.
