Grayscale Research: Bitcoin's "Digital Gold" Narrative Faces Test, Price Action More Resembling High-Risk Growth Asset

As $NEAR drops, trader 0xec90 just had 748,091 $NEAR ($3.67M) liquidated!

After Chinese cross-border brokers including Futu, Tiger Brokers, Longbridge, and Huasheng Securities, some Hong Kong-based Chinese securities firms have also started clearing their existing mainland China operations. To comply with relevant regulatory requirements, Guotai Junan International has implemented partial adjustments to services for its existing mainland investor accounts starting from the 26th of this month. According to customer service staff at Guotai Junan International, these adjustments are similar to measures previously taken by brokers such as Futu Holdings and Tiger International: when existing mainland investor accounts log in from mainland China (with login IPs showing as domestic), they will be unable to deposit funds or place buy orders, only allowing fund withdrawals or sell transactions. If an account’s login IP is located outside mainland China, its fund transfer and trading functions remain unaffected. If a customer obtains a new identity, they must update their corresponding document information; as holders of overseas documents, such customers will not be subject to this rule.

Beating AI Insight News Brief: Developer David has open-sourced Jevgrep, a research tool built on Jev specifically for coding agents to locate code. Users only need to ask a question like "Where is the login validation implemented?" and it uses TypeSafe’s Jev decision model to search the codebase layer by layer, identifying relevant files and source code snippets before passing them to agents such as Claude Code and Codex for further modification and testing. It primarily addresses the token-intensive "code lookup" step that coding agents face. Jevgrep does not feed the entire repository to the model upfront, nor does it rely solely on a single semantic search. It first determines which directories are worth exploring further, then checks relevant files and code declarations, and finally returns source code snippets, line numbers, and follow-up reading references. The repository also includes a "Skill" that enables agents to know when to call `jg` to gather context. The latest SWE-bench experiment used 10 Python tasks. Both with and without Jevgrep, 8 tasks were completed, but the total cost for GPT-5.6 Sol dropped from $7.62 to $5.44, a reduction of 28.63%. The author initially stated a 40% reduction on X, but later updated the experiment results in the repository, revising it to "around 30%". However, this figure only accounts for Sol’s costs and does not include Jev’s expenses. The confirmed Jev call costs in the experiment logs amount to at least $1.57, while some calls lack complete billing records, so the actual total is unknown. Additionally, the experiment only included 10 tasks, with each run only once.

According to TradingBeats' monitoring, crypto market maker Wintermute currently holds approximately $93 million in short positions and around $5.12 million in long positions on Hyperliquid. The position breakdown is as follows: ETH short positions worth ~$47.19 million, with an unrealized profit of ~$490,000, entry price of $2,682.86, and liquidation price of $5,398.49; SOL short positions ~$11.39 million, unrealized profit ~$100,000, entry price $119.64, liquidation price $623.73; HYPE short positions ~$10.04 million, unrealized profit ~$240,000, entry price $92.02, liquidation price $498.65; DOGE short positions ~$7.25 million, unrealized profit ~$190,000, entry price $0.10, liquidation price $0.68; XRP short positions ~$6.02 million, unrealized profit ~$150,000, entry price $1.53, liquidation price $13.43; BTC long positions ~$5.12 million, entry price $82,888.30; PUMP short positions ~$5.03 million, unrealized loss ~$400,000, liquidation price $0.05; ENA short positions ~$3.08 million, unrealized loss ~$230,000, entry price $0.24, liquidation price $4.17; SUI short positions ~$2.65 million, unrealized profit ~$10,000, entry price $1.18, liquidation price $21.61.

Benson Sun, founder of Coinkarma, says the practical value of liquidation heatmaps is vastly overestimated. Many traders now spot a large cluster of liquidations at a certain price level and immediately interpret it as "the price will definitely go to sweep this area". However, liquidation charts themselves rely heavily on assumptions. Most liquidation heatmaps work by taking historical market trading data and plugging in a set of hypothetical leverage multiples—such as 5x, 10x, 20x, 30x, and 50x—to reverse-engineer the price levels where those positions "might" be liquidated after trading. As a result, the dense liquidation zones users see do not actually represent an identical number of positions waiting to be liquidated there; too many variables are at play. Those traders may have already exited their positions. Some may add to their positions, some may reduce them, and others may top up margin. As long as position size, margin, or average cost changes, the liquidation heatmap shifts. The longer the time frame, the larger this error becomes. Therefore, the most useful window for liquidation heatmaps is roughly the last 24 hours to 3 days. Using liquidation clusters from 7 days, 30 days, or even months ago as current "magnet price levels" is meaningless. Liquidation heatmaps can serve as auxiliary information for short-term market structure analysis, but they should not play a major role in a trading system, as they easily create a false sense of certainty. There will always be liquidation clusters above and below the price. When prices rise, it is said they will first sweep the short positions above; when prices fall, it is said they will first sweep the long positions below; if prices fall first then rise, it is said they will first sweep longs then shorts. In any case, there is an after-the-fact explanation, and it is hard to falsify beforehand—this makes it not an analytical tool, but pure pseudoscience.

According to market data from BIT (bit.com), the U.S. 10-year Treasury yield has risen to 5.234%, hitting its highest level since mid-2007. The 30-year Treasury yield climbed to 5.542%, the highest since 2004. This indicates a significant rise in the market’s pricing of long-term risk, with growing concerns over persistent inflation, the Federal Reserve’s maintenance of high interest rates, as well as massive fiscal deficits and debt sustainability. Long-term borrowing costs for governments, corporations and consumers have been pushed up, which typically suppresses stock market valuations, tightens global financial conditions, and may curb economic growth to some extent. For more analysis, see the article "U.S. Long and Short-Term Treasury Yield Curves Nearing Inversion: Is a Recession Precursor Signal Activated?"