Tesla's 4.45% Slide Driven by Record $44.87B Volume on October 7 2025

On October 7, 2025, Tesla (TSLA) saw a 4.45% decline, closing with a trading volume of $44.87 billion—the highest on the day's market. The stock's performance was influenced by a mix of operational updates and market sentiment shifts, with analysts noting heightened sensitivity to macroeconomic signals.

Recent reports highlighted production challenges at Tesla's Berlin and Texas facilities, citing supply chain bottlenecks and labor adjustments. These factors, combined with mixed quarterly earnings expectations, contributed to investor caution. Additionally, regulatory scrutiny over autonomous driving trials in key markets added short-term uncertainty, though long-term growth projections for EV adoption remained unchanged.

To carry out this back-test rigorously I need to pin down (and, in some cases, confirm) a few implementation details: 1. Universe • Which market should we draw the “top-500-by-volume” list from each day? (e.g., all U.S. common stocks, only S&P 1500 constituents, another specific universe, etc.) 2. Trade timing & pricing • Do we rank on each day’s closing volume, buy at that same close, and liquidate at the next day’s close (1-day holding period)? • Or do you prefer “rank at today’s close → buy next day’s open → sell next day’s close”? 3. Position sizing • Equal-weight across the 500 names (i.e., 0.2 % of capital in each), or another weighting scheme? 4. Practical note on tooling • The current back-test engine exposed here handles one ticker at a time. To implement a daily 500-stock rotation we would need either (a) a custom cross-sectional engine (not available in this chat toolset) or (b) an approximation—e.g., test the strategy on a proxy such as an equal-weighted portfolio index if one exists. • Let me know if a proxy is acceptable; otherwise, I can outline how to run the strategy offline in Python and provide step-by-step code.