Barclays strategists have pointed out that the apparent calm shrouding the US stock market for months is masking unprecedented volatility in individual stocks. Last year served as clear evidence: although the S&P 500 index recorded a 16% gain led by the artificial intelligence (AI) boom, some of its largest components experienced exceptionally sharp swings. According to Barclays' statistics, among the index's top 100 constituents, there were 47 instances of severe sell-offs—specifically, declines of five standard deviations or more, a type of extreme movement typically considered an anomaly. This marks the highest record since the bank began tracking the data in 1998. Barclays believes that more such occurrences are likely this year. This judgment partly underscores just how reliant the benchmark index has become on the performance of stocks tied to the AI theme. However, the bank also noted that it equally illustrates how AI technology itself is accelerating the speed at which traders react to market-moving events. "Individual stocks have become the epicenter of volatility," stated Stefano Pascale, Head of US Equity Derivatives Research at Barclays, during a telephone interview. He indicated that this environment is fostering a "lottery mentality" among retail traders. On Wednesday, even as the S&P 500 fell 0.5% and investors sold tech stocks, a closely watched volatility measure for the index remained below its 2025 average. Barclays' research suggests that retail investors buying during stock price dips is one factor suppressing overall market volatility. Over the next month or so, a series of events could pose shock risks to the S&P 500, which just hit a record high on Monday. For investors looking to hedge against a renewed rise in index volatility, Christopher Jacobson, a strategist at Susquehanna International Group, recommended buying put options on the SPDR S&P 500 ETF Trust with a strike price of $685, while the ETF closed around $690 on Wednesday. Specifically, he mentioned contracts expiring on February 6 in his Wednesday report. He stated this would provide investors with risk protection through a series of key events: including the main phase of the big tech earnings season, the Fed's policy decision on January 28, the employment report on February 6, and a potential Supreme Court tariff ruling, not to mention growing global geopolitical concerns. Currently, expectations for significant broad market volatility are low. But Barclays strategists predict that intense turbulence in certain individual stocks is highly likely to disrupt the overall calm. They advise navigating this dynamic through a "dispersion trading" strategy, which involves using derivatives to bet on individual stock volatility increasing against a backdrop of relative broad market tranquility. As the earnings season unfolds, the timing for employing this strategy may be ripe. Last year, some of the S&P 500's largest components saw enormous single-day swings, such as Oracle Corp. (ORCL.US) surging 36% on September 10 due to an earnings surprise, and UnitedHealth Group Inc. (UNH.US) plunging 22% on April 17 following an earnings disappointment. Pascale, along with Anshul Gupta, Head of EMEA Derivatives Research at Barclays, pointed out that increasingly sophisticated technology, particularly AI, is enabling analysts and traders to use algorithms to parse quarterly results within seconds. Gupta noted that this has ended the "post-earnings announcement drift," the former trend where stocks would gradually adjust over several days following an earnings report. Barclays indicated that while risks surrounding earnings have become more concentrated, it has also become more difficult to distinguish winners from losers amidst the pervasive AI frenzy. "There is significant divergence among individual stocks, and investors need to target specific names," Pascale said. "The era where an AI bubble or AI boom lifted all boats is over."
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