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Institutional ETF Flows Tilt Toward This Altcoin in February

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Solana ETF flows in February

Solana exchange-traded funds (ETFs) are diverging from broader crypto ETF trends this month. While demand for Bitcoin and Ethereum products has shown signs of cooling, Solana-linked funds have maintained steady inflows.

The shift comes amid heightened volatility in digital asset markets. With macro uncertainty weighing on investor sentiment, ETF flows may be offering a signal of where institutional capital is positioning in the short term.

Solana ETF Streak Stands Out in Volatile Crypto Market

According to data from SoSoValue, Solana ETFs have recorded consecutive inflows since February 10. As of February 24, the products have logged only three red days this month. Overall, the ETFs have pulled in $30.33 million. 

The streak stands out against the more uneven performance seen in larger crypto ETFs during the same period.

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Solana ETF flows in February
Solana ETF flows in February. Source: SoSoValue

Bitcoin ETFs have posted mixed results in February. Inflows were recorded on seven trading days this month. Ethereum ETFs have followed a similar pattern, reflecting inconsistent demand rather than sustained accumulation. 

Despite those positive sessions, cumulative flows remain deeply negative. So far this month, Bitcoin ETFs’ net outflows stand at $939.94 million. In addition, Ethereum ETFs recorded outflows of $490.58 million.

When compared to other altcoin products, Solana’s performance also appears relatively stronger. XRP-linked ETFs have experienced outflows on three trading sessions this month while recording zero flows on four days. 

Although the number of positive sessions is comparable, the consistency of Solana’s streak since mid-February remains notable.

Nonetheless, it is important to contextualize the data. In absolute dollar terms, inflows into Solana ETFs remain smaller than those seen in Bitcoin products. 

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Bitcoin and Ethereum ETFs continue to command the majority of institutional crypto exposure and overall capital allocation. However, consistency in flows can indicate relative resilience in demand during periods of broader uncertainty.

The steady inflows into Solana products suggest that some investors are maintaining or selectively increasing exposure to higher-beta assets, even as flagship crypto ETFs experience uneven demand. Still, the divergence may reflect short-term capital rotation rather than a structural shift in institutional positioning.

SOL Price Remains Under Pressure 

Despite the ETF inflows, Solana’s price performance has continued to reflect broader market weakness. Like most major digital assets, SOL has trended downward over the past month, declining 32.8%.

The altcoin saw a modest recovery today, rising more than 7% as total crypto market capitalization expanded by approximately $32 billion. At press time, SOL was trading at $82.15.

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Solana (SOL) Price Performance.
Solana (SOL) Price Performance. Source: BeInCrypto Markets

However, technical analysts remain cautious on the asset’s near-term outlook. Market commentator Alejandro suggested that Solana’s next downside target could be $45.

Whale Factor described the token as entering a high-probability “make or break” zone on the 4-hour chart. According to the analysis, SOL’s wedge formation is “reaching maximum exhaustion,” signaling a potential volatility squeeze at a critical inflection point.

The analyst outlined two possible scenarios:

“Bull Case: Clean break and retest of $82 targets the $97-100 macro resistance. Bear Case: Failure to hold the $78 support level opens the door for a retest of $68.”

Whether Solana will extend its recovery or face renewed downside pressure remains to be seen.

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Crypto World

Tether Unveils AI System to Run Large Models on Smartphones

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Tether Unveils AI System to Run Large Models on Smartphones

Tether, issuer of the world’s largest stablecoin by market cap, USDT, has released a new AI training framework that it says allows large language models to be fine-tuned on consumer hardware, including smartphones and non-Nvidia GPUs.

According to Tuesday’s announcement, the system, part of its QVAC platform, uses Microsoft’s BitNet architecture and LoRA techniques to reduce memory and compute requirements, potentially lowering the cost and hardware barriers to developing AI models.

The framework supports cross-platform training and inference across a range of chips, including AMD, Intel and Apple Silicon, as well as mobile GPUs from Qualcomm and Apple.

Tether said its engineers were able to fine-tune models with up to 1 billion parameters on smartphones in under two hours, and smaller models in minutes, with support extending to models as large as 13 billion parameters on mobile devices.

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