The cryptocurrency market continues its overall downward trend amidst tensions. Bitcoin (BTC) has fallen nearly 5% over the past 12 hours and is currently trading at around 126.89 million won. Outflows from spot ETFs and risk aversion are cited as factors driving the selling pressure.
The macroeconomic environment in the market is strengthening Bitcoin's safe-haven value in the medium term due to the US Federal Reserve's quantitative easing and the weak dollar. However, the short-term trend remains negative. In particular, the movement of 2,188 BTC by a large whale suggests a rebalancing of positions by major holders, adding to market volatility.
Ethereum (ETH) is also showing weakness, following the market trend. Currently trading at around 4.26 million won, it has recorded a short-term decline of nearly 9%. However, the movement of institutional whales accumulating around 100,000 ETH is interpreted as a positive sign for long-term holding.
Ripple (XRP) and Solana (SOL) also failed to avoid the downtrend. Ripple is currently trading at around 2,702 won, and while there are no major technical issues, it is being affected by market-wide risk aversion. Solana is trading at around 177,000 won, and token unlock issues are putting additional downward pressure on its price.
Recently, approximately 90 billion won worth of leverage liquidations occurred in the cryptocurrency market, contributing to volatility. A sharp price drop triggers forced liquidations, creating a feedback loop that further fuels further price declines.
Additionally, ongoing token unlock schedules for various projects are raising investor concerns. Consequently, schedules for projects like Pi Network and Humanity Protocol are posing short-term risks for altcoins.
Regulatoryly, major countries such as Spain, Russia, and the United States are announcing ETF-related regulations. While this is positive in terms of institutionalizing cryptocurrencies, it has not led to a short-term price rebound.
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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