ConocoPhillips’ 25% Workforce Cut Drives $890M Trading Volume as Oil Sector Tackles Oversupply and Economic Uncertainty

, , . The move, aimed at streamlining operations and reducing costs, reflects broader challenges in the oil sector, including oversupply from OPEC+ and economic uncertainty. The layoffs, , signal a shift in focus toward capital discipline amid falling oil prices and earnings.

Analysts highlighted the company’s struggle to balance long-term projects, such as the high-cost Willow oil venture in Alaska and its liquefied natural gas expansion, with immediate cost control. CEO acknowledged rising per-barrel costs since 2021 and emphasized the need to eliminate non-value-adding activities. . .

. However, critics argue the company must address capital allocation more rigorously to remain competitive. Despite these challenges, ConocoPhillips retains strong U.S. shale assets in the Permian, Eagle Ford, and Bakken, where operational efficiencies are expected to reduce labor needs.

To run this back-test accurately I’ll need to pin down a few practical details: 1. Universe of stocks • Should we screen the entire U.S. common-stock universe (all listed U.S. equities), or limit it to a benchmark universe such as the Russell 3000 or S&P 1500? • If you have another market (e.g., China A-shares, Europe, etc.) in mind, please let me know. 2. Trade execution assumptions • Typical practice is: – Pick the top-500 names by today’s dollar volume (or share volume) at the close. – Enter at the next day’s open, exit at that same day’s close (1-day holding period). • If you’d prefer “buy at today’s close, sell at tomorrow’s close” or another convention, just say so. 3. Transaction costs / slippage • Should we include a round-trip cost assumption (e.g., 2 bps per side) or ignore costs? Once we have these points clarified I can pull the necessary data, generate the daily signals, and run the portfolio back-test from 2022-01-03 (first trading day of 2022) through today.