ETFs and high-net-worth retail accounts opened Bitcoin to institutions, but the influx was modest. Derivatives and the sheer size of the market make price manipulation harder, flattening volatility while also limiting upside.
The Federal Reserve's shift to a gradual, modest balance-sheet expansion limits macro stimulus for Bitcoin. At the same time, liquidity and M2 have begun to diverge, creating occasional price-decoupling, while cheap oil keeps inflation in check, influencing mining economics.
Analysts flag the $60,000 level as a critical liquidation point for Bitcoin, with support expected near $50-$55k if the price breaks lower.
Robinhood and Coinbase have invested because Lighter offers a bridge between traditional brokerage services and DeFi, but institutional participation requires on-chain KYC and regulatory-friendly designs to overcome the cold-start liquidity problem.
Hyperliquid's on-chain transparency lets anyone see positions, stop-losses and liquidation points, enabling price discrimination that rewards trustworthy traders and penalizes toxic high-frequency actors.
Hyperliquid positions itself as the "AWS of liquidity", abstracting away exchange complexity so developers can focus on building applications. By creating a general-purpose L1 with native order-book primitives and a Builder-code SDK, the protocol enables anyone to launch regional exchanges or novel financial products.
A three-pillared daily bias--market structure, liquidity draw, and price-direction (PD) race--guides trade selection. Aligning higher-time-frame bias with lower-time-frame order flow filters out noise and improves win rates.
Understanding each currency pair's unique volatility, swap, and liquidity profile lets traders tailor entry aggressiveness and position sizing, turning a generic strategy into a personal edge.
Specific hour-long windows around major market openings (London, New York) provide higher probability setups. Outside those windows, price tends to consolidate, so traders should focus on high-volume periods.
Nang details how large orders move prices, the role of VWAP algorithms, and why the "iceberg" effect creates self-reinforcing price moves.