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 of 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.

GenInnov

Innovation Fund for post GenAI world

“Samsung Electronics: A Whale in a Lake”—that’s how I described the South Korean leviathan back in the late nineties when I was heading an equity research team based in Seoul. In 1999, the behemoth had begun dominating so much, and this was before the arrival of its flat-screen products and mobile phones, that its profits were larger than all the 160+ technology companies of the Japan tech index put together. And yet, Samsung Electronics’ market cap was less than 2% of the aggregate Japanese tech market cap. I would hear all sorts of justifications for the SEC’s deep discount to all tech companies globally (it was the third largest profit-making company in the world at the time), but none too convincing.

At the other extreme of market pricing was Taiwan: in a similar role, while based in Taipei in the mid-2000s, I found a ridiculously simple, disciplined strategy to keep outperforming in the local equities. If one invested in the top ten companies on the sales growth charts every month, such a portfolio would trounce the local index by over 15% a year, post trading costs. Taiwanese firms, unique in their practice of announcing monthly sales figures by a fixed date, created a different momentum nature for the market.

The simple momentum strategy for Mumbai, my next market, turned out to be previous periods’ price winners. One can surely deploy better momentum strategies, but the simple nature of some of these strategies and anomalies provide more than a counterargument to efficient market theories.

There’s no universal rhythm to listed markets. Different sectors, eras, and even companies move to unique beats. Take the current AI frenzy around LLMs: talk to a non-US company, and the focus is on the lack of monetization. Their US counterparts, facing similar challenges, sing a different song – one of rapid development and future potential.

Logically, one would expect these disparate perspectives to remain disparate forever or lead to great equalization over time. In fact, it is neither, or both, or either that one knows much later! Investing in markets is different from investing in businesses. As in the Taiwan example, a nuanced understanding of businesses is not a prerequisite for success in equity markets. That said, investing through the learning of business currents also creates great portfolios for long-term success.  

This week, amidst a turbulent market, it’s crucial to remember where the true melody lies: in the businesses, the products, the innovations. Share prices will gyrate, grabbing headlines and influencing decisions, but they shouldn’t drown out the progress. Just look at the Boston Dynamics video from this week – a symphony of technological advancement. Or the exciting announcements from Google, Intel, Meta, Baidu, and others – each a new verse in the ongoing composition of innovation. These are the stories that matter, the ones that drive long-term value

GenInnov

Innovation Fund for post GenAI world