Hedge funds are revisiting volatility dispersion trades as widening gaps between individual U.S. stocks create fresh opportunities, according to a Bloomberg report cited by BlockBeats on Sept. 27. The setup is being driven by three overlapping forces: the growing divide between AI winners and losers, sharp moves in energy shares tied to developments involving Iran and Ukraine, and rising U.S. Treasury yields.
The strategy typically involves buying options on individual stocks while selling options on the S&P 500, a structure designed to capture larger differences in stock-specific volatility while hedging broader market swings. Bloomberg said the trade has gained appeal as AI affects sectors such as software, banking and travel in uneven ways, while energy producers and refiners have also started moving apart.
Data from Nomura showed that the one-month realized absolute return dispersion of S&P 500 constituents relative to the index has climbed to the 95th percentile of the past 30 years. At the same time, implied volatility on single stocks has eased since late July, lowering entry costs for the strategy. Still, the trade is not without risk. Ambrus Group co-chief investment officer Kris Sidial warned that it could face crowded positioning and concentrated unwinds. With earnings season approaching, uncertainty around AI’s effect on corporate profits and industry structure could keep stock moves sharply differentiated, while some companies with heavy AI exposure may see steep declines.
Hedge funds are turning back to volatility dispersion trades as a wider split across U.S. equities opens up new setups, according to Bloomberg in a report cited by BlockBeats on Sept. 27.
Bloomberg said three forces are driving the move: a growing divide between winners and losers in the AI sector, sharp swings in energy stocks linked to developments involving Iran and Ukraine, and rising U.S. Treasury yields. Together, those factors are pushing stock-level performance further apart across the U.S. market.
The trade usually involves buying options on individual stocks and selling options on the S&P 500 index. The goal is to bet that volatility differences among index constituents will widen, while hedging overall market volatility at the same time.
The opportunity set has expanded as AI affects software, banking and travel in increasingly different ways. Bloomberg also pointed to a divergence between energy producers and refiners, adding another source of stock-specific volatility.
Nomura data showed that the one-month realized absolute return dispersion of S&P 500 constituents relative to the index has risen to the 95th percentile over the past 30 years. At the same time, implied volatility on individual stocks has declined since late July, reducing the cost of entering the trade.
There are still risks. The strategy has been popular for years, and the market has concerns about crowded positioning. Kris Sidial, co-chief investment officer at hedge fund Ambrus Group, said the trade could face the risk of a concentrated unwind.
With earnings season approaching, uncertainty remains over how AI will affect corporate profits and industry structure. That could push individual stock performance even further apart, though some companies with high exposure to AI-related risks could also see sharp declines.
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