AI, Nvidia’s Ascent, and Sleepy Stock Analysts

Few stock stories can match that of Nvidia. Its market value skyrocketed by an astounding $2.5 trillion in under two years—an increase surpassing the value of the stock markets of all but ten countries—catching even seasoned analysts off guard!

In this post, I will explore why stock analysts failed to predict Nvidia’s phenomenal profit surge propelled by AI adoption.

Stock Analysts and Market Dynamics

When I buy a company’s stock, like Nvidia’s, I bet on its future profitability. Forecasting that future is challenging for amateurs, which is where stock analysts come in. They provide insights that help investors make informed decisions.

Analysts critically examine a company’s financial results and gather information from various sources, including management, customers, suppliers, and competitors. When pieced together accurately, this data offers a reasonably reliable picture of a company’s future performance.

Investment banks and brokerage firms employ analysts to forecast revenues and profits, periodically publishing research reports recommending whether to buy, hold, or sell stocks. The average of these forecasts serves as a benchmark for a firm’s expected performance and influences investor behavior and stock valuation.

Stock Mispricing

Stock prices are constantly in flux and are often misvalued due to market sentiment, misinformation, manipulation, and general market inefficiencies.

Even though mispricing is common, Nvidia’s case, highlighted next, is glaring.

Nvidia’s Remarkable Rise

In under two years, from October 2022 to June 2024, Nvidia’s stock price soared about 1100% while the S&P 500 grew 57%, with Nvidia significantly contributing to that growth.

This explosive rise underscores how undervalued Nvidia was in late 2022—something most analysts failed to recognize.

Nvidia was not an under-the-radar firm, its unphonetic name notwithstanding; it has long been a leader in producing cutting-edge chips, and top analysts closely monitor the firm. How could they have been oblivious to its immediate potential?

Reasons for Analysts’ Shortcomings

To dissect this analytical failure, let’s examine three key factors.

1. Disruptive Technologies

Predicting the impact of disruptive technologies is inherently challenging, especially when looking far into the future. Near-term predictions are much more attainable, but that didn’t hold for Nvidia.

At the start of the third quarter of 2022, analysts were clueless about Nvidia’s impending stellar performance in 2023 and 2024. They struggled to forecast this performance, even as its stock began creeping up following the launch of ChatGPT on November 30, 2022.

The AI revolution was gaining momentum, with Nvidia at its epicenter, yet analysts underestimated both the rapid adoption of AI and the critical role of Nvidia’s processors in these applications.

Interestingly, even as a non-expert, I sensed significant AI-driven changes were imminent long before ChatGPT was released. My email program had started suggesting intelligent, pre-written responses, signaling advancements in natural language processing. News about self-driving car tests from Tesla also highlighted early AI developments. These developments motivated me to write a blog post in September 2022 about AI powering my college WhatsApp group (you can read the post [here]).

Analysts’ failure to predict Nvidia’s near-term rise reflects not just the complexities of disruptive technologies but also analysts’ lack of initiative and foresight regarding a shift they should have anticipated. Their subpar performance can be attributed partially to the two factors discussed next.

2. Career Motivations.

Analysts, like most professionals, are influenced by career considerations. When they deviate from consensus predictions, the career repercussions can be significant if they are wrong. For instance, earlier this year, Marko Kolanovic, JP Morgan’s chief equity strategist, was let go after repeatedly forecasting a market decline even as the market continued to rise and most analysts were bullish.

Conversely, analysts with standout predictions can achieve superstar status if proven correct, as Meredith Whitney at Oppenheimer did by flagging the mortgage-backed securities crisis.

Yet, no prominent analyst pounded the table when Nvidia’s stock price was less than one-tenth of its current price in October 2022. This reluctance may have stemmed from career concerns; some analysts may have surmised Nvidia’s imminent rise, but they chose caution.

Even otherwise, the inherent risks of predicting disruptive technologies might often lead career-conscious analysts to focus on short-term trends over transformative changes, resulting in the situation discussed here.

3. Distribution of Finance Talent

Finance attracts some of the brightest undergraduates, drawn by high salaries and the allure of Wall Street. Many top undergraduates aim for investment banking roles, while equity research attracts less accomplished talent.

After their two-year stints, the best investment banking analysts often move to private equity firms or hedge funds, where any equity research they do is confidential.

Even at the MBA level, second or lower-tier MBA program candidates often fill equity research positions.

While equity research analysts are talented, their analytical skills, innovative thinking, and initiative might not be of the levels required to navigate complex market conditions. This talent gap can affect the quality of their analyses, likely contributing to Nvidia-type situations.

Conclusion

The Nvidia example exposes critical flaws in market efficiency and raises concerns about the reliability of expert guidance.

Despite their significant resources and industry insights, analysts failed to foresee  Nvidia’s meteoric rise—an oversight potentially stemming from career concerns and talent gaps besides the inherent challenges of predicting disruptive technologies.

Nvidia’s stock analysts particularly failed retail and small institutional investors, who are especially vulnerable to such oversight. As AI and other emerging technologies reshape industries, should we look up to analysts who missed the mark, or should we rely more on our insights?

Note

I have focused on stock analysts in this post. But others, including prominent hedge, pension, and mutual funds, also lagged in this instance.