Grayscale debuts Avalanche staking ETF on Nasdaq

Grayscale Investments announced Thursday that its Grayscale Avalanche Staking ETF (GAVA) has begun trading on Nasdaq, offering investors a new exchange-traded product tied to the Avalanche ecosystem.

The fund seeks to provide exposure to AVAX, the native token of the Avalanche network, while also incorporating staking to potentially capture rewards generated through participation in the network’s Proof of Stake consensus model.

The launch of GAVA reflects ongoing investor interest in accessible investment vehicles that incorporate digital assets into traditional portfolios, said Inkoo Kang, Senior Vice President of ETFs at Grayscale.

Originally launched as a private placement in August 2024, the product now expands Grayscale’s lineup of digital asset investment vehicles.

“GAVA complements our existing suite of more than 40 digital asset products and provides investors with the ability to gain exposure to one of the market’s leading smart contract platforms, supported by Grayscale’s scale, research, and infrastructure,” Kang noted.

Avalanche is a smart contract platform designed to overcome common blockchain limitations by distributing core functions across multiple chains responsible for transactions, smart contracts, and network coordination.

The network separates key functions across three integrated chains responsible for digital asset transfers, smart contract execution, and validator coordination.

According to Grayscale, this architecture, combined with customizable Avalanche L1 blockchains, enables developers and enterprises to build tailored blockchain environments while maintaining overall network performance.

“Avalanche was designed from day one to support real-world applications at scale,” said John Wu, President of Ava Labs. “Built for business, Avalanche enables financial services, enterprise platforms, and tokenized real-world assets through a customizable, flexible architecture that gives institutions the performance, security, and control needed for production deployment.”

Disclosure: This article was edited by Vivian Nguyen. For more information on how we create and review content, see our Editorial Policy.

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