7 min read
Welcome to the most volatile decade in recent memory—and we’re not even halfway through.
The 2020s has already recorded 440 trading days with daily stock movements of 1 per cent or more, according to wealth manager Ben Carlson.
To put that in perspective, an entire decade typically averages just 507 such days.
Said another way, the 2020s have crammed nearly 10 years of stock market volatility into less than five years — an unusually heavy dose of ups and downs.
So, if you are feeling the stock market is moving faster, now you know why.
When markets are volatile, the common advice is to simply tune out the noise.
But it’s easier said than done.
The problem lies in the way our brain processes information.
In the book Your Money and Your Brain, author Jason Zweig said our brains are wired to recognise patterns even when none exist.
Here’s the rub: it’s not a mechanism you can switch off at will.
In other words, by watching daily stock price movements, you may be receiving the wrong signals and end up learning the wrong lessons.
That’s a big problem as key misconceptions may start to take shape.
Take the sudden rise of China’s DeepSeek AI model back in January.
When the news broke, AI-related stocks were hammered, with Nvidia (NASDAQ: NVDA) bearing the brunt, suffering a 17 per cent fall in a single day.
Such a sequence suggests you need to react fast to avoid such a mishap.
Furthermore, it also implies the need to instantly assess new developments and act to prevent further losses.
But that’s not how it played out.
In both cases, investors are misled into thinking that speed is the difference between making and losing money.
In the hours and days after DeepSeek became mainstream, the narrative quickly centred around the Chinese AI model’s development cost — under US$6 million.
Why was this figure important?
This low expense stood in contrast to the billions of dollars US companies were pouring into AI models and data centres, with Nvidia taking the lion’s share.
Hence, the prevailing narrative suggested that Nvidia would have the most to lose.
Yet, six months later, it’s becoming clear that the hasty assessment on DeepSeek is premature in more ways than one.
One, DeepSeek’s US$6 million development cost does not cover any prior research and experiment on data, architectures, and algorithms.
Translation: the actual cost is higher but unknown, effectively knocking out the main narrative.
Two, major tech companies such as Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta Platforms (NASDAQ: META) and Microsoft (NASDAQ: MSFT) have continued to pour billions into data centres.
