The Bitwise NEAR ETF (NRR) launched on NYSE Arca in late September 2026 as the first U.S.-listed spot NEAR exchange-traded product. It aims to track the CME CF NEAR Protocol–Dollar Reference Rate – New York Variant, which reflects the U.S.-dollar price of NEAR on major platforms.
NRR is a passively managed, single-asset fund that holds NEAR directly. Its portfolio is 100% concentrated in the token, with an expense ratio of 0.75%. Coinbase Custody Trust Company serves as custodian, keeping private keys in cold storage. Bitwise stakes substantially all of the fund’s NEAR holdings and passes a portion of the rewards into the NAV, targeting an annualized staking yield of about 5%.
I checked comparable single-asset crypto ETFs using Tickeron’s AI Screener to see how NRR’s concentration compares with peers. This concentrated setup means the ETF moves almost in lockstep with the NEAR token, which helps explain its recent volatility.
Over the trailing 30 days, NRR has fallen approximately 27%, moving from a closing price near $25.13 to roughly $18.29. The drop has featured sharp daily swings rather than a steady decline.
Since its September debut near $26.15, the fund has declined roughly 30%. It reached a 52-week high of $29.64 in mid-October before reversing, losing more than one-third of its value from peak to trough.
The slide largely tracks a correction in the NEAR token after its autumn rally. NEAR rose from below $2.50 in mid-September to nearly $5.90 in mid-October, attracting leveraged positions. As broader digital-asset markets pulled back, forced long liquidations in NEAR perpetual futures sped up the decline, with funding rates easing and open interest contracting.
Additional pressures included a collective selloff in artificial intelligence-themed crypto assets, where NEAR fell faster than the broader group due to its high-beta positioning. Macro uncertainty around U.S. midterm elections weighed on risk appetite. In mid-November, NEAR AI reported a limited security incident that paused a cloud inference service, though the main chain, tokens, and wallets remained unaffected. Early post-launch fund flows also moderated in early November.
NRR’s short history aligns closely with the NEAR token’s boom-and-retrace pattern. Early gains reflected institutional interest in new spot crypto products and enthusiasm for NEAR’s agentic-commerce narrative, with cumulative NEAR Intents volume crossing the $32 billion mark.
The reversal stemmed from cooling speculative positioning rather than any network failure. A governance proposal to cut NEAR’s maximum annual issuance from 2.5% to 1.6% over 24 months was approved, which is structurally positive, though implementation is not expected until early 2027. The quarter shows how quickly sentiment-driven inflows and leverage can reverse in single-asset vehicles.
Broad digital-asset risk appetite and Bitcoin’s direction will remain important, given that altcoin ETFs often show higher beta to overall crypto sentiment. The AI-and-blockchain narrative, including NEAR Intents volume growth and AI Cloud adoption, will help determine whether fundamentals support renewed demand.
Investors should also watch the rollout of the issuance reduction, staking participation levels, and whether ETF inflows resume after the early-November pause. Regulatory developments around spot crypto products and staking-enabled funds add another layer. As a single-asset, high-volatility vehicle, NRR stays sensitive to shifts in leverage, funding rates, and open interest in NEAR derivatives.
I find Tickeron’s AI-powered tools helpful when evaluating concentrated products like this. The AI Screener lets investors scan thousands of securities with technical indicators, fundamentals, volatility metrics, price patterns, and AI-generated signals to compare momentum and signal strength across the market. For single-asset cryptocurrency ETFs such as NRR, it provides a structured way to assess volatility and performance relative to other opportunities. Explore the AI Screener to begin filtering the market with data-driven tools.
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