Hedge Funds Focus on Volatility Trading, AI, Oil Prices, and U.S. Treasury Yields Impacting Divergence in U.S. Stocks

On September 27, the competition between winners and losers in the AI industry, the volatility of energy stocks triggered by the situations in Iran and Ukraine, and the rise in U.S. Treasury yields have led to a divergence in the performance of individual U.S. stocks, prompting hedge funds to refocus on volatility dispersion trading strategies. This strategy involves buying individual stock options and selling S&P 500 index options, betting on the widening volatility differences among constituent stocks while hedging against overall market volatility. The impact of AI on industries such as software, banking, and travel is becoming increasingly differentiated, with price movements of energy producers and refiners showing disparities, thus increasing trading opportunities. According to Nomura Securities, the degree of divergence in the actual absolute returns of S&P 500 constituent stocks relative to the index has risen to the 95th percentile of the past 30 years. Since the end of July, the implied volatility of individual stocks has decreased, lowering the entry costs for related strategies. However, this strategy has been popular for many years, raising concerns about overcrowded trading in the market. Kris Sidial, co-CIO of hedge fund Ambrus Group, believes that this trade may face risks of concentrated liquidation. As the earnings season approaches, the impact of AI on corporate profits and industry dynamics remains uncertain, and the performance of individual stocks may further diverge, with some companies highly exposed to AI risks potentially experiencing significant declines.

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