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Bitcoin's traditional four-year market cycle, once a cornerstone of crypto market analysis, is now obsolete, according to Arthur Hayes, co-founder of BitMEX and CIO of Maelstrom. In a detailed essay titled "Long Live the King," Hayes argues that Bitcoin's price movements are increasingly dictated by global liquidity conditions rather than the programmed supply constraints of halving events. This shift, he contends, is driven by the interplay of U.S. and Chinese monetary policies, institutional adoption of
ETFs, and structural changes in global capital flows [1].Historically, Bitcoin's bull markets have aligned with periods of monetary expansion. Hayes highlights three key eras: the 2013 surge linked to U.S. quantitative easing and Chinese infrastructure credit, the 2017 ICO boom fueled by yuan devaluation and credit growth, and the 2020–2021 pandemic-driven rally supported by U.S. fiscal stimulus. In each case, Bitcoin's price peaks coincided with liquidity surges rather than halving events [1]. The current cycle, Hayes asserts, follows the same logic, with the U.S. Treasury injecting $2.5 trillion in liquidity through short-term bill issuance and the Federal Reserve signaling a 94% probability of a rate cut in October 2025 [1].
China's role in this new paradigm is equally critical. Beijing's shift from deflationary policies to mild easing has created a complementary liquidity environment, reinforcing Bitcoin's upward trajectory. Hayes notes that China's credit expansion, while less aggressive than in previous cycles, avoids tightening that could otherwise undermine Bitcoin's gains [1]. This alignment of U.S. and Chinese monetary policies, he argues, forms the foundation of a new structural regime for Bitcoin in 2025, where liquidity, not supply events, dictates market dynamics [1].
Institutional adoption has further amplified the impact of liquidity. Research from K33 underscores this trend, showing that Bitcoin's all-time high of $126,199 in 2025 coincided with a record 63,083 BTC accumulation via ETFs and futures in a single week. These inflows, coupled with regulatory clarity and open interest growth, have created a feedback loop where monetary policy directly influences Bitcoin's price [1]. Meanwhile, U.S. President Donald Trump's advocacy for looser fiscal policies and lower interest rates-aimed at stimulating growth and reducing debt-further supports a prolonged liquidity-driven bull market [2].
The Federal Reserve's easing stance, with expected rate cuts totaling up to 100 basis points over 12 months, and China's PBOC's accommodative policies suggest liquidity will remain abundant through 2026. Hayes predicts this environment could extend Bitcoin's rally beyond the traditional four-year timeline, emphasizing that "money itself now sets the cycle" [2].
Market data reinforces this thesis. Bitcoin's price has risen alongside global M2 money supply growth, a metric tracking cash, deposits, and liquidity. Historical correlations show Bitcoin rallies during periods of monetary expansion, such as the 2008 financial crisis, the 2016 European Central Bank stimulus, and the 2020–2021 pandemic response [6]. Current conditions mirror these patterns, with central banks worldwide-particularly in the U.S., China, and Japan-projecting rate cuts to support economic activity .
ETF inflows have also played a pivotal role. BlackRock's iShares Bitcoin Trust (IBIT) alone recorded $899 million in inflows on October 7, 2025, while Bitcoin spot ETFs saw $441 million in weekly inflows over eight consecutive days. These figures highlight institutional confidence in Bitcoin as a hedge against fiat depreciation and a core component of global asset allocation .
Hayes' analysis has gained traction among analysts. Matthew Hougan of Bitwise and K33 Research's Vetle Lunde argue that the four-year cycle is effectively obsolete, with Bitcoin's price now driven by structural forces like ETF adoption and geopolitical liquidity shifts. As central banks continue to prioritize growth over tightening, Bitcoin's trajectory appears increasingly tied to macroeconomic conditions rather than algorithmic supply constraints [3].

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