SoundHound Shares Drop 6.57% on $1.01 Billion Volume as Liquidity-Driven Strategy Back-Test Ranks 128th in U.S. Market

Generated by AI AgentAinvest Volume Radar
Friday, Oct 10, 2025 7:58 pm ET1min read
SOUN--
Aime RobotAime Summary

- SoundHound shares fell 6.57% on $1.01B volume, ranking 128th in U.S. market.

- Decline linked to proposed liquidity-driven strategy back-test using top 500 U.S. stocks by volume.

- Framework specifies execution rules, equal-weight allocation, and performance metrics like Sharpe ratios.

- Requires validation of filters and assumptions before generating trade signals and historical analysis.

SoundHound Inc. (SOUN) fell 6.57% on October 10, 2025, with a trading volume of $1.01 billion, ranking 128th among U.S.-listed equities. The decline followed a strategic back-test framework proposal aimed at evaluating liquidity-driven trading strategies across a defined universe of U.S. stocks.

The proposed methodology outlines a 500-stock universe from NYSE and NASDAQ, excluding ADRs and ETFs. It specifies execution rules based on daily closing volumes, with trades executed at the next day’s open and closed at the close. Equal-weight allocation is applied to the top 500 volume-ranked names, using a 2022-01-03 to 2025-10-10 timeframe. Parameters include potential filters for minimum price thresholds and daily notional trading volume to exclude illiquid securities.

Implementation requires confirmation of assumptions such as price and market-cap filters. Once validated, the process will generate daily trade signals for the “Top-500-by-volume” list, calculate cumulative returns, annualized performance, volatility metrics, Sharpe ratios, and maximum drawdowns, alongside equity curve visualizations. The framework assumes no transaction costs or slippage, aligning with common conventions for short-horizon liquidity strategies.

To run this back-test accurately, the following details must be finalized: universe composition, execution conventions, date ranges, and additional constraints. Upon confirmation, the system will pull historical volume and price data, generate trade signals, and execute the back-test to produce performance metrics.

Hunt down the stocks with explosive trading volume.

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