While the virtual asset market continues to experience mixed trends, major virtual assets are exhibiting divergent trends. Bitcoin (BTC) and Ethereum (ETH) are maintaining their upward trend, while Solana (SOL) is recording a strong surge, drawing market attention. Conversely, Ripple (XRP) is gradually rising, fueled by growing expectations for its adoption within the Japanese financial system.
Bitcoin is currently trading at around 127.72 million won, up 1.63% over the past 24 hours amid continued interest from institutional investors. The derivatives market is particularly evident in its expansion, projected to reach approximately $85.7 trillion this year. This suggests increasing institutional participation. The US GENIUS Act and Europe's MiCA regulations are believed to have contributed to bolstering market confidence.
Ethereum is trading at 4.27 million won, up 1.18%. While it lacks independent momentum, it is trending upward, following Bitcoin's lead. There are currently no ETF or regulatory issues in the market, and its movements are driven by the portfolio compositions of institutional investors.
Ripple rose 1.05%, trading at 2,720 won. Expectations for long-term value growth are rising as the possibility of XRP being integrated into Japan's foreign exchange and payment systems grows. Experts predict that XRP could move beyond being a mere speculative asset and become a core component of a cross-border payment network.
Solana is trading at 178,000 won, showing a sharp rise. While some unusual percentage points have been reported, the strong upward trend remains. As a high-beta asset with growing risk appetite, Solana is exhibiting particularly resilient price movements, reflecting the bull market.
Overall, the virtual asset market is being reorganized around themes such as institutionalization, the expansion of derivatives, and regulatory clarity. A notable characteristic is that each major coin is strengthening its unique role within this trend.
TokenPost AI Notes
This article was summarized using a TokenPost.ai-based language model. Key points in the text may be omitted or inaccurate.
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