Salesforce Slides to 34th in Liquidity with $2.04B Volume as Tech Turbulence Overshadows AI-Driven Optimism

. 12, 2025, , . equities by liquidity. The selloff occurred amid broader tech sector volatility as investors digested earnings reports and macroeconomic signals ahead of the Federal Reserve’s policy decision cycle.

Analysts noted muted demand for cloud software stocks following mixed guidance from enterprise SaaS peers. Salesforce’s shares were pressured by renewed concerns over customer acquisition costs and long-term contract visibility, despite recent product launches in AI-driven CRM tools. Institutional selling activity intensified during afternoon trading as rebalanced positions in high-beta technology names.

Market structure data revealed a widening bid-ask spread in the final hour of trading, reflecting reduced market maker participation. Short-term technical indicators showed bearish divergence between price action and volume profiles, suggesting potential for further consolidation below key support levels established in early August.

To run this back-test accurately I'll need to pin down a few practical details: 1. Universe - Are we talking about all U.S. listed common stocks, or a specific index/universe? 2. Ranking logic - The full day's volume is only known after the close. Do you want to: a) Rank stocks on yesterday's volume and enter at today's open, or b) Rank on today's volume and enter at today's close (which is less realistic to execute intraday)? 3. Trade price - Use the day's open price for entry and the next day's open for exit, or use closes? 4. Weighting - Equal-weight the 500 names each day, or value-weight by (say) dollar turnover? 5. Risk controls - Any stop-loss, take-profit, or max holding-days rules beyond the 1-day hold? (If none, I'll assume no additional risk controls.) Once those points are confirmed I can set the data retrieval plan and run the back-test.