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Global Equity Derivatives Strategy Summary

Core Content

This document provides an analysis of the US and EU equity markets focusing on earnings dispersion, stock correlations, and the potential for volatility through the Q4 earnings season. It introduces the concept of "Gamma Rentals" as a strategy to identify pairs of stocks that are likely to move significantly in relation to each other during earnings reporting.

Main Views

• Earnings Dispersion and Volatility:

  • In 2024, earnings growth for Tech+ stocks was significantly higher than the rest of the S&P 500, resulting in a $24.5%$ spread.
  • For 2025, the spread is expected to narrow to $10.4%$, but the dispersion remains a key feature of the market.
  • High earnings dispersion contributes to low index correlations, which is a trend that is likely to persist.

• Gamma Rentals Framework:

  • The framework screens for stocks that are likely to move together through earnings.
  • The hit rate of top 50 pairs producing positive delta-hedged P&L dropped to the long-run average of ~60% in Q3, compared to ~85% in Q2.
  • The strategy involves identifying stocks with direct peers reporting earnings prior to their own, to capture 'sympathy' moves.

• Top US Gamma Rental Candidates:

  • The top 20 US stocks for pairwise volatility include: GOOG, FRT, DVN, AME, ESS, AVGO, OXY, IRM, BEN, TROW, MPC, HUM, BKNG, PFE, OKE, MAA, AVB, PSX, MU, and CTAS.
  • Sectors with the most attractive pairwise volatility: Real Estate, Energy, Financials, and Tech.

• Top EU Gamma Rental Candidates:

  • The top 20 EU stocks for pairwise volatility include: SOI FP, HUSQB SS, STERV FH, VNA GY, BMW GY, KINVB SS, TLX GY, EKTAB SS, LEG GY, UPM FH, CPR IM, FNTN GY, PRY IM, ALFA SS, MTX GY, FRO NO, SREN SE, ALV GY, VOE AV, and BG AV.
  • Sectors with the most attractive pairwise volatility: Real Estate, Tech, Energy, and Consumer Discretionary.

Key Information

• Earnings Convergence:

  • A break in the AI tailwind could lead to earnings convergence, which would result in higher stock correlations and potentially higher volatility.

• Sector Analysis:

  • In the US, Financials (especially Regional and Large Cap Banks), and Semis show the highest realized correlation relative to implied.
  • Retail, Homebuilders, Biotech, and Software show the highest dispersion.

• Growth Conundrum:

  • The document highlights a key question: Can NVIDIA (NVDA) grow revenues without hyperscalers growing capital expenditures (capex)? This is a central issue in the earnings dispersion dynamics.

• Performance Metrics:

  • The framework uses a composite ranking of pairwise backtest, quantitative signal, and volatility carry.
  • It also includes report dates and correlation scores for each pair, which are crucial for timing and strategy execution.

Figures and Data

• Figure 1: Compares S&P 500 historical average implied moves with realized-implied beat rates.
• Figure 2: Compares S&P 500 vs. sector-level aggregate implied vs. realized earnings moves for 2Q24.
• Figure 3: Shows S&P 500 1m realized correlation vs. earnings seasons.
• Figure 4: Displays S&P 500 consensus 2025 EPS revisions.
• Figure 5: Illustrates the 3m realized-implied correlation spread by index and (sub)sector.
• Figure 6: Highlights the discrepancy between NVIDIA revenue and hyperscaler capex as a key earnings driver in 2025.

Summary

The document outlines a strategy for identifying stocks that are likely to experience significant price movements during the Q4 earnings season. It emphasizes the importance of earnings dispersion and the role of the Gamma Rentals framework in capturing correlated moves. The analysis includes top stocks and sectors in both the US and EU markets, with a focus on the potential impact of AI on earnings trends. The key takeaway is that while earnings dispersion is expected to decrease in 2025, it remains a significant factor in market volatility and correlation. The strategy is supported by detailed performance metrics and data visualizations to guide investment decisions.