Figma’s 10.13% Plunge Hits 122nd in $1.04B Volume Surge

Generated by AI AgentAinvest Volume Radar
Friday, Oct 10, 2025 8:33 pm ET1min read
FIG--
Aime RobotAime Summary

- Figma (FIG) fell 10.13% on Oct 10, its biggest drop since IPO, with $1.04B volume (32.58% surge).

- The selloff aligned with mixed market breadth signals and macroeconomic sensitivity amid sector rotation.

- Analysts noted underperformance vs peers despite broader sector shifts, highlighting volatility risks.

Figma (FIG) closed on October 10 with a 10.13% decline, marking its largest single-day drop since its market debut. The stock saw a surge in trading activity, with a $1.04 billion volume—a 32.58% increase from the previous day—ranking it 122nd among all equities in daily trading. The selloff coincided with mixed signals from market breadth strategies, as high-volume names struggled to maintain momentum in a volatile session. Analysts noted the drop occurred amid broader sector rotation but highlighted Figma’s underperformance relative to its peers.

Recent developments surrounding FigmaFIG-- remain centered on its strategic positioning in the design software space. While no direct company-specific news triggered the sharp decline, market participants observed heightened sensitivity to macroeconomic factors. The stock’s price action aligns with broader trends of profit-taking following its recent consolidation phase. Short-term traders are now closely monitoring key support levels as volatility remains elevated.

For the proposed backtesting scenario—a multi-stock, daily-rebalanced portfolio targeting the 500 highest-volume names—current constraints limit execution to single-security analysis. Two viable alternatives include constructing an equal-weight synthetic index of the 500 names or using a broad-market proxy like SPY/RSP. Custom data preparation would be required for the synthetic index approach, while the ETF method simplifies testing but may dilute strategy specificity. Further clarification is needed to determine the optimal path forward for evaluating this high-frequency trading model.

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