[Hedge Funds Bet on 'Volatility Trading'; AI, Oil Prices, and U.S. Treasury Triple Shock Ignite U.S. Stock Divergence] BlockBeats News, September 27, according to Bloomberg, the battle between winners and losers in the AI industry, the sharp fluctuations in energy stocks triggered by the situations in Iran and Ukraine, and the rise in U.S. Treasury yields are driving further divergence in individual U.S. stock movements, prompting hedge funds to revisit the 'volatility dispersion trading' strategy. This strategy typically involves buying single-stock options and selling S&P 500 index options, betting on the widening volatility differences among constituent stocks while hedging overall market volatility. As AI's impact on industries such as software, banking, and tourism becomes increasingly differentiated, and as stock price movements among energy producers and refiners diverge, trading opportunities have increased. According to data from Nomura Securities, the degree of divergence between the one-month actual absolute returns of S&P 500 constituent stocks relative to the index has risen to the 95th percentile over the past 30 years. Meanwhile, since late July, implied volatility for individual stocks has declined, reducing the entry cost for related strategies. However, this strategy has been popular for years, and concerns about overcrowded trades in the market persist. Kris Sidial, Co-Chief Investment Officer of hedge fund Ambrus Group, believes this trade may face risks of concentrated unwinding. As earnings season approaches, the impact of AI on corporate profits and industry dynamics remains highly uncertain, potentially leading to further divergence in individual stock movements. However, some companies highly exposed to AI risks may also experience significant declines. [Original Link]