The US stock market's "surface calm" hides individual stock earthquakes: AI frenzy breeds extreme volatility and a "lottery mentality"

The strategist of Barclays PLC Sponsored ADR pointed out that beneath the calm surface that has enveloped the US stock market for the past few months, unprecedented volatility in individual stocks is lurking. Last year was a clear example: despite the S&P 500 index recording a 16% increase led by the artificial intelligence (AI) boom, some of its largest component stocks experienced abnormal fluctuations. According to Barclays' statistics, there were a total of 47 instances of drastic sell-offs among the top 100 constituents of the index - specifically referring to a decline of five standard deviations or more, a trend that is usually considered anomalous. This is the highest record the bank has seen since data has been available since 1998. Barclays believes that similar situations may arise this year. This assessment partly highlights how dependent benchmark indices have become on the performance of stocks related to the AI theme. However, the bank also points out that this demonstrates how AI technology itself has accelerated traders' speed in reacting to market events. "Individual stocks have become the center of volatility," said Stefano Pascale, head of Barclays' US stock derivatives research, in a phone interview. He pointed out that this environment has fostered a "lottery mentality" among retail traders. On Wednesday, despite a 0.5% drop in the S&P 500 index and investors selling off tech stocks, a closely watched volatility indicator for the index remained below the average level of 2025. Barclays' research indicates that retail investors buying on price declines are one of the factors restraining overall market volatility. Over the next month or so, a series of events may pose risks to the S&P 500 index, which just set a new all-time high on Monday. For investors hoping to hedge against a resurgence in index volatility, Susquehanna International Group strategist Christopher Jacobson recommends buying put options on the SPDR S&P 500 ETF Trust with a strike price of $685, while the ETF's closing price on Wednesday was around $690. Specifically, he mentioned contracts expiring on February 6th in his report on Wednesday. He stated that this would provide investors with risk protection throughout a series of key events, including the major tech stock earnings season, the Federal Reserve's policy decision on January 28th, the jobs report on February 6th, and the potential upcoming Supreme Court ruling on tariffs, not to mention increasing global economic concerns. Currently, the market's expectations for significant overall market volatility are low. However, Barclays strategists predict that the severe fluctuations in certain individual stocks are likely to disrupt this overall calm. They recommend using a "dispersed trading" strategy to address this dynamic, which involves using derivatives to bet on increased volatility in individual stocks against a backdrop of relatively subdued markets. As earnings season unfolds, the timing may be right to adopt this strategy. Last year, some of the largest stocks in the S&P 500 index experienced massive single-day fluctuations, such as Oracle Corporation on September 10th skyrocketing 36% due to a surprise in earnings, and UnitedHealth Group Incorporated dropping 22% on April 17th due to an unexpected earnings report. Pascale and Anshul Gupta, head of Barclays' derivatives research for Europe, the Middle East, and Africa, pointed out that increasingly sophisticated technology, particularly AI, is enabling analysts and traders to analyze quarterly performances in a matter of seconds using algorithms. Gupta stated that this has put an end to the "post-earnings drift," a trend where stocks have traditionally adjusted gradually in the days following earnings announcements. Barclays notes that while the risks surrounding earnings reports have become more concentrated, in the widespread AI boom, distinguishing winners from losers has also become more difficult. "There is a significant differentiation between individual stocks, and investors need to target specific stocks," Pascale said. "The era of the AI bubble or the AI boom lifting all stocks is over."