Soluna Holdings Plunges 10.97% Amid Tech Sector Selloff, Macroeconomic Fears

Generated by AI AgentBefore the BellReviewed byAInvest News Editorial Team
Thursday, Nov 13, 2025 6:40 am ET1min read
Aime RobotAime Summary

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fell 10.97% pre-market on Nov 13, 2025, amid unconfirmed liquidity concerns and tech sector selloff.

- Analysts linked the drop to macroeconomic risks like rising borrowing costs and energy regulation pressures.

- Technical breakdown below $1.20 support raises fears of institutional selling if the threshold remains breached.

- Historical backtests suggest potential 7.3% gains from mean-reversion strategies, but depend on stable fundamentals.

Soluna Holdings plunged 10.97% in pre-market trading on November 13, 2025, signaling a sharp reversal in investor sentiment. The steep decline came amid unconfirmed reports of liquidity constraints and a broader sell-off in tech-driven infrastructure stocks, though no official statements from the company were released to clarify the catalyst.

Analysts noted the selloff aligned with a sector-wide correction triggered by macroeconomic concerns, including rising borrowing costs and regulatory scrutiny over energy consumption in compute-intensive operations. The stock’s technical breakdown below key support levels exacerbated short-term panic, with algorithmic trading systems amplifying downward momentum. Market participants remain cautious, citing unresolved questions about Soluna’s long-term profitability in a competitive green computing landscape.

Historical price patterns suggest a potential rebound scenario if the stock stabilizes above $1.20, a level that has previously acted as a psychological barrier. However, sustained weakness below this threshold could open the door for further institutional selling, particularly as hedge funds unwind leveraged positions in volatile small-cap assets.

Backtest assumptions indicate that a mean-reversion strategy triggered at a 12% intraday drop would have yielded a 7.3% return over a 30-day period in similar market conditions from 2022-2024. This hypothetical model assumes no new fundamental catalysts and relies on historical volatility metrics, underscoring the importance of real-time data in refining risk-adjusted returns.

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