Betting on the overall stability of the S&P 500 index while individual stocks experience significant fluctuations has long been a popular and reliable strategy among hedge funds. However, as the volatility of individual stock prices rises to extreme levels, reverse trading is gradually attracting investors' attention.
According to data from the Chicago Board Options Exchange (CBOE), an indicator measuring the dispersion of large-cap U.S. stocks over the next month has climbed to its highest level since 2020, while the implied correlation among the top 50 components of the S&P 500 index is nearing a historical low.
Although during earnings season, it is common for stock price movements to diverge due to varying company fundamentals, when correlation is extremely lacking, the entire market becomes highly vulnerable once macro events trigger synchronized market movements.
Adapt Investment Managers is one of the hedge funds betting on a return of index volatility and a convergence in individual stock movements.
"Reverse dispersion trading remains one of our core holdings," said Alexis Maubourguet, Chief Investment Officer at Adapt Investment Managers, in a telephone interview. He noted that traditional standard dispersion trading is currently "extremely crowded."
Implied Correlation Hits a Low, Gravitational Pull for Reversion Strengthens
This year, as implied correlation has fallen toward historical lows, reverse dispersion trading has been under pressure. Maubourguet admitted that this strategy performed the worst last quarter, but he remains optimistic about the current environment, believing that reverse trading could deliver excess returns once a volatility shock occurs.
"We believe that from the perspective of mathematical asymmetry, reverse dispersion trading is highly attractive," he said. "This aligns closely with the fund's investment philosophy—we are willing to bear small localized losses in exchange for asymmetric large gains."
CBOE data shows that the three-month implied correlation once dropped to a historical low of about 7% this month and is currently only slightly above that level.
David Elms, Head of Diversified Alternatives at Janus Henderson Group plc, believes that reverse dispersion trading could profit if correlation reverts to its historical average. He pointed out that the 10-year average implied correlation for the S&P 500 index is 33%, and it even exceeded 80% during the COVID-19 pandemic.
Elms stated: "Implied correlation effectively has a lower bound of zero, so trades that are long implied correlation—such as reverse dispersion strategies—have a favorable asymmetric return profile when correlation reverts to the mean." Based on this, he considers reverse dispersion trading "more attractive" than traditional strategies.
With dispersion and correlation indicators already at extreme levels, some buy-side institutions are beginning to take a cautious stance on traditional dispersion trading.
"At current levels, investors are hesitant to enter, and more clients are starting to discuss reverse operations," said Mandy Xu, Head of Derivatives Market Intelligence at CBOE. "That is, shorting dispersion and going long correlation, because current trading has deviated to extreme levels."
AI Rotation and Earnings Season Amplify Individual Stock Divergence
The divergence between individual stocks and the index is also driven by the start of earnings season and investor sector rotation.
Wells Fargo Securities noted that the options market expects greater volatility in individual stocks this earnings season, while the overall S&P 500 index reaction will be relatively muted. "We are in an earnings environment where structural individual stock reactions are more intense," strategist Ohsung Kwon said in an interview.
He believes that movements in the artificial intelligence (AI) sector are largely driving the significant volatility in individual stocks. "This dispersion trend is logical," he added, noting that rotation between sectors is also accelerating, while the overall index remains largely flat.
The sharp volatility in tech stocks was particularly evident in the second quarter. Since March, both the realized and implied volatility of the "Magnificent Seven" stocks have far exceeded that of the S&P 500 index, with the initial impact from the Iran conflict and the surge in oil prices gradually fading.
Even so, given that earnings surprises and other unexpected news could trigger sharp fluctuations in individual stocks, some investors focused on reverse trading remain cautious.
"Although standard dispersion trading is still performing well, some investors have decided to reverse their positions, that is, selling individual stock volatility and buying index volatility," said Kieran Diamond, derivatives strategist at UBS Group. "To avoid excessive short volatility exposure on individual stocks, such trades are typically balanced by over-weighting long positions in the index."
Another possible reason for the narrowing overall volatility of the S&P 500 index is the diminishing impact of economic data on the broader market. The current dominant market narrative remains the tug-of-war between investors' fear of missing out (FOMO) on AI and tech giants and risk-off sentiment.
Citigroup pointed out that the correlation between the S&P 500 index and economic data surprises is continuing to weaken. Strategist Scott Chronert wrote in a July 10 report that his "Pulse" chart "shows the correlation between the S&P 500 and economic data surprises is approaching negative territory, a multi-year trend."
Despite dispersion trading remaining popular, even as entry costs have risen, the current extreme market levels are making reverse strategies appear more attractive.
"Every successful high-dispersion trade each month attracts more capital into that strategy direction," said Adapt's Maubourguet. "Reverse dispersion trading has never had such favorable positioning conditions as it does now."
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