Public Inc. Navigates Sector-Wide Apathy as $300M Volume Ranks 375th in U.S. Equity Volume Shares Dip 0.20% Amid Regulatory Shifts and Earnings Uncertainty

On October 6, 2025, Public Inc. (ticker: PEG) recorded a trading volume of $300 million, ranking 375th among U.S.-listed equities for the day. The stock closed down 0.20% against broader market trends, reflecting muted investor activity amid sector-specific dynamics.

Recent developments highlight shifting investor sentiment toward utility-sector plays. A regulatory update on renewable energy incentives in key markets has sparked speculation about long-term capital allocation for infrastructure projects. Analysts note that Public’s exposure to regulated assets may offer downside protection, though near-term earnings visibility remains constrained by delayed project timelines.

Market participants are closely monitoring the company’s upcoming quarterly earnings report, with particular focus on its balance sheet resilience amid rising interest rates. Institutional trading patterns suggest a defensive positioning strategy, with reduced open interest in leveraged options contracts compared to prior reporting periods.

To make sure the test is set up exactly the way you have in mind, could you please confirm a few implementation details? 1. Market universe • Do we screen all U.S.-listed common stocks (NYSE + NASDAQ + ARCA), or a different market/universe? 2. “Trading volume” definition • Rank by share volume (shares traded) or by dollar volume (shares × price)? 3. Timing convention • Entry: use yesterday’s ranking and buy at today’s open? • Exit: sell at today’s close (same-day hold) or tomorrow’s close (1 full trading-day hold)? 4. Frictional costs • Assume zero transaction fees/slippage, or apply a cost per trade? 5. Tool limitation (multi-asset portfolios) • Our backtest engine is designed for a single-ticker or event-based study. For a 500-stock daily-rebalanced portfolio, we need to build a custom return series first, then feed it into the engine. Are you comfortable with that approach? Once I have these details I can generate the data-retrieval plan and run the back-test immediately.