How Earnings, Volatility, and AI Capex Are Affecting US Markets

Market Context & Earnings Outlook

• The S&P 500 financial sector reached an all-time high as half of the large banks reported earnings, with 20% of S&P market cap scheduled to report next week.
• Analysts project a 22% year-on-year earnings growth for U.S. equities, setting a high fundamental bar.
• Options markets imply a 5.5% average move for S&P stocks, which is 60–70 basis points higher than the long-run average.
• Approximately 75% of global equities bought off the April lows were sold heading into earnings, resulting in relatively "clean" investor positioning.
• Investors face tension between momentum factors and high single-stock realized volatility despite low index realized volatility.

AI Infrastructure & Credit Markets

• Hyperscalers and AI infrastructure providers require $5.5 to $6 trillion in capital between 2025 and 2030 to fund build-outs.
• Major AI companies are transitioning from asset-light to asset-heavy models, leading them to tap credit markets after previously focusing on equity buybacks.
• Goldman Sachs' hyperscaler bond basket widened by 22 basis points last week due to supply concerns and market concentration.
• Issued and pipeline bond sizes are creating capacity constraints for fixed income investors already holding high levels of tech exposure.
• A widening disparity exists between credit protection (CDS) costs for hyperscalers versus "pure-play" AI names, indicating divergent market anxiety levels.

Volatility Dynamics & ETF Structures

• Global realized correlation is at historically low levels, with muted index volatility masking extreme single-stock volatility.
• The KOSPI implied volatility is currently higher than levels seen during the Global Financial Crisis.
• Korean market volatility is driven by extreme concentration in a few "100-ball" stocks and aggressive ETF structuring.
• Year-to-date, 33% of newly issued ETFs contain leverage or inverse components, compared to the standard 20% universe average.
• Large leveraged ETFs create significant short gamma exposure, forcing forced selling during downturns and buying during rallies based on AUM size.
• The liquidity footprint of rebalancing is determined by the absolute size of the ETF (e.g., $20 billion vs. $1 million) rather than just the presence of leverage.

Goldman Sachs Trading Recommendations

• Trade 1: Single-Stock Collars. Investors should buy 10% out-of-the-money puts on long equity positions, funding them by selling 15–20% out-of-the-money calls.
  • This strategy capitalizes on anomalous implied volatility where call options in 10% of S&P names and 15% of NASDAQ names trade at higher implied vol than puts.
• Trade 2: Downside Leveraged Exposure. Investors are suggested to purchase binary "one-touch" put options on the S&P 500.
  • Targeting a 7% index drop by late August offers 5x leverage for a $1 payout.
  • Targeting a 10% drop offers 10x leverage for a $1 payout.
  • This trade exploits the low cost of index-level protection driven by compressed index volatility.

Forward-Looking Focus & Risks

• Market attention is shifting to inflation data, specifically the upcoming PCE print at the end of July.
• The Federal Reserve's FOMC meeting at month-end is a key catalyst following the appointment of a new Fed head.
• Employment data is considered stable, with the primary economic risk centering on inflation persistence and economic management.