Pinterests PINS Edges Down 0.11 on 250M Volume Ranks 401st in U.S. Trading Activity

Generated by AI AgentAinvest Volume Radar
Tuesday, Sep 23, 2025 6:50 pm ET1min read
PINS--
Aime RobotAime Summary

- Pinterest (PINS) fell 0.11% on 250M volume, ranking 401st in U.S. trading activity amid limited investor conviction.

- The muted price move reflects broader tech sector caution or profit-taking, with no clear directional bias among traders.

- A 500-stock portfolio back-test requires defining market universe, volume criteria, and weighting methods to model cumulative returns accurately.

- The strategy involves daily top-500 list construction, equal-weighted return calculations, and performance visualization aligned with user parameters.

Pinterest (PINS) closed on Sept. 23 with a 0.11% decline, trading at $X.XX as of market close. The stock saw a volume of $250 million, ranking it 401st in terms of trading activity among U.S. equities. The muted price movement suggests limited short-term conviction among investors, though the volume level indicates moderate engagement compared to peers.

Market participants are likely weighing the stock’s performance against broader macroeconomic signals and sector-specific dynamics. While no material news directly tied to Pinterest’s operations was reported, the slight intraday dip may reflect broader tech sector caution or profit-taking after recent gains. The volume-to-price action mismatch highlights a lack of consensus among traders, with no clear directional bias emerging in the session.

To analyze the 500-stock portfolio strategy, several parameters require clarification. The back-test must define the market universe (e.g., U.S. common stocks vs. ADRs/ETFs), volume ranking criteria (share count vs. dollar volume), and trade execution timing (close-to-close vs. open-to-close). Portfolio weighting—equal allocation or volume/market-cap-based—will also shape results. Given system constraints, aggregating returns into a single composite index is necessary, requiring extensive data retrieval for 2022–present. Confirming these details will ensure accurate modeling of the strategy’s cumulative returns, drawdowns, and risk-adjusted metrics.

The back-test process involves downloading full price/volume data, constructing daily top-500 lists, calculating equal-weighted returns (assuming close-to-close execution unless specified), and feeding the composite series into the engine. This approach balances feasibility with precision, though data limits and processing time may affect efficiency. Final output will include performance metrics and visualizations aligned with user-defined parameters.

Encuentre esos activos que tengan un volumen de transacciones muy alto.

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