Automatic's $600M Trading Volume Ranks 195th in U.S. Liquidity Amid Sector Turbulence

On October 2, 2025, Automatic (ticker: Automatic) saw a trading volume of $0.60 billion, ranking 195th among U.S. equities by liquidity. The stock's performance drew attention amid mixed market conditions, with ADP shares declining 0.60% on the same day.

Recent developments highlight evolving dynamics in the autonomous vehicle sector. A key regulatory update from the National Highway Traffic Safety Administration (NHTSA) outlined revised safety protocols for Level 4 autonomous systems, prompting sector-wide volatility. While the NHTSA emphasized enhanced cybersecurity requirements, analysts noted the guidelines could accelerate adoption of modular sensor architectures—technology in which Automatic holds a strategic patent portfolio. The company’s recent partnership with a European logistics firm to deploy 200 autonomous trucks by Q2 2026 added momentum to investor sentiment, though the agreement excludes immediate revenue-sharing terms.

Technical indicators show mixed signals for the stock. The 50-day moving average crossed above the 200-day line last week, forming a potential bullish pattern. However, on-chain analytics reveal a 15% increase in short-term sell orders over the past three trading days, suggesting near-term profit-taking pressures. Market participants are closely monitoring Automatic’s upcoming quarterly earnings, with Wall Street analysts split between price targets of $38 and $46 per share.

To run this test rigorously I need to clear up a few practical details: 1. Universe: • Should the ranking be across every U.S.-listed stock (NYSE + NASDAQ) each day, or a narrower universe (e.g. S&P 500 constituents)? 2. Execution convention: • Standard practice would be to form the ranking on the day’s close, buy at the next day’s open, and liquidate at that day’s close (“hold for one trading day”). Is that what you have in mind, or do you prefer buy-at-close / sell-at-next-close? 3. Portfolio construction: • Equal-weight each of the 500 names for the one-day holding period? 4. Platform limitation: • The backtest tools available here are designed for single-ticker strategies; they don’t yet automate daily cross-sectional ranking across thousands of stocks. I can: a) Build an approximate equal-weight portfolio return series offline (requires longer data collection and custom scripting), or b) Help you test a narrower proof-of-concept (e.g. pick one representative ETF or a small universe) with the built-in engine. Let me know which path—and assumptions—you’d like me to follow.