ARKM -62.11% in 24 Hours Amid Selloff and Redemption Flows

On AUG 31, 2025, ARKM dropped by 62.11% within 24 hours to reach $0.481, ARKM dropped by 476.19% within 7 days, dropped by 303.03% within 1 month, and dropped by 6536.8% within 1 year.

ARKM, the actively managed exchange-traded fund (ETF) focused on disruptive innovation and technology equities, has seen an unprecedented decline in its share price over the past 24 hours. The fund, which has historically been a proxy for high-growth tech and biotech stocks, fell sharply amid a broad selloff in risk assets. The drop marks one of the most extreme intraday declines in the fund’s history. The decline follows a recent wave of redemptions and reduced liquidity in the underlying components, which have been under increasing pressure due to macroeconomic conditions and a shift in investor sentiment toward more defensive assets.

Technical indicators have shown deteriorating momentum across the fund’s holdings, with bearish divergence evident in RSI levels and a steepening bearish channel on the 1-hour chart. Analysts have noted that ARKM’s exposure to high-beta assets makes it particularly susceptible to volatility in broader markets, especially amid rising interest rates and tightening credit conditions. The fund’s net asset value (NAV) has also declined sharply in recent weeks, with the discount to NAV widening significantly due to liquidity constraints.

Backtest Hypothesis
A recent backtesting strategy explored the efficacy of a mean-reversion approach in managing ARKM-related exposure. The strategy, which involved entering long positions following periods of extreme bearish momentum and exiting at overbought thresholds, was tested using historical price data. The results indicated that such a strategy would have captured several rebounds amid sharp declines. However, the backtest also highlighted the challenges of executing the strategy in real time, particularly when liquidity is constrained and spreads are wide. Given the recent performance, the backtesting model suggests that volatility is likely to remain elevated, necessitating a more nuanced approach that accounts for both directional bias and liquidity conditions.