On Wednesday afternoon, Nvidia joined the $3 trillion market cap club along with Apple and Microsoft. It may be a temporary membership, but it seems every time Jensen Huang, CEO of Nvidia, makes a speech, the stock goes up. In my 60+ years I have seen many companies which seemed to have only the moon as a limit. History has shown us differently. In this blog post, I will share some research on bubbles I remember and end with comments on Nvidia.
The tulip mania, also known as tulipomania, which occurred in the Netherlands during the 17th century Dutch Golden Age is considered the first recorded instance of an asset bubble. The Rise of the tulip started when they were introduced to Holland (now Netherlands) from the Ottoman Empire in the late 16th century. Their exotic beauty and rarity quickly captured the attention of the wealthy and the growing middle class. A peculiar characteristic of tulips, a virus which caused streaked and variegated coloring, became especially desirable, further inflating their value.
By the 1630s, tulip bulbs were not just seen as beautiful flowers but as potential investments. People began buying and selling tulip bulb contracts, often for future delivery, hoping to profit from rising prices. This speculation drove prices to extraordinary heights. A single tulip bulb at the time could be worth more than a house or several years of an average person’s salary.
And then came the Crash. The bubble couldn’t be sustained. By February 1637, the market for tulip bulb contracts collapsed abruptly. There is a debate about the exact cause of the crash, but factors like a lack of actual tulips to fulfill contracts and a dwindling number of interested buyers likely contributed. Many who had speculated heavily on tulips lost significant amounts of money.
There is a legacy to the story. The tulip mania serves as a historical cautionary tale about the dangers of speculative bubbles in financial markets. It highlights how asset prices can become detached from their intrinsic value and the potential for sudden crashes.
The U.S. stock market is full of stories of meteoric rises and spectacular crashes. The episodes are often referred to as bubbles. Following are ten examples of stocks which once seemed headed for the moon.
These stories serve as a reminder of the dangers of bubbles and the importance of considering both potential and reality when making investment decisions. These are just a few examples of stocks that were once thought to be unstoppable. There are many other examples throughout history.
Several factors can cause stock market bubbles to burst, including rising interest rates, loss of confidence, and excessive speculation. Speculation can drive stock prices to unsustainable levels, and when the bubble bursts, prices can fall sharply. No stock is guaranteed to go up forever.
What about Nvidia? Whether Nvidia’s stock price is a bubble is a complex question analysts are debating. An argument for Nvidia being a bubble is the high valuation: Nvidia’s stock price has surged significantly in recent years, leading to a high price-to-earnings (P/E) ratio. This suggests the stock price may be inflated compared to the company’s actual earnings.
A second factor is competition. The chip market is competitive, and Nvidia faces challenges from established players such as Intel, AMD, and emerging rivals. Some major customers may decide to design their own chips like Apple did. Increased competition could put pressure on margins and growth. A broader economic slowdown could dampen demand for Nvidia’s products.
On the other hand, Nvidia has a strong track record of innovation and revenue growth. The company is a leader in the growing field of AI and graphics processing units (GPUs) which are also in high demand. The market for AI and GPUs is vast and continues to expand, providing Nvidia with significant growth potential. Ultimately, whether Nvidia’s stock is a bubble depends on the market’s investment horizon and risk tolerance.
Note 1: The image of tulips was generated by an AI in WordPress.
Note 2: I use Gemini AI and other AI chatbots as my research assistants. AI can boost productivity for anyone who creates content. Sometimes I get incorrect data from AI, and when something looks suspicious, I dig deeper. Sometimes the data varies by sources where AI finds it. I take responsibility for my posts and if anyone spots an error, I will appreciate knowing it, and will correct it.
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