Bitcoin at the crossroads: why its fate is tied to the collapse of the tech bubble

December 11 marked a critical inflection point for the markets. Oracle announced disappointing results that eroded $80 billion of its market capitalization, while simultaneously revealing plans to increase capital expenditure on AI infrastructure from $35 billion to $50 billion, partially financed through debt increases. The stock plummeted 16%, triggering a domino effect that dragged Nvidia, AMD, and the Nasdaq lower. On the same day, Bitcoin fell below $90,000.

This event was no coincidence. It reveals an emerging structural vulnerability in Bitcoin: it has become the most volatile instrument within the tech betting ecosystem, responding in an amplified manner to sentiment shifts in AI-related stocks.

The trap of high correlation

Recent data analysis demonstrates the degree of entanglement between Bitcoin and the tech sector. Before Nvidia’s reports in November, the Pearson correlation between Bitcoin and Nvidia reached approximately 0.96 over a three-month rolling window—practically perfect. Regarding the overall Nasdaq, the 30-day Pearson correlation coefficient registered 0.53 as of December 10.

This contrasts dramatically with Bitcoin’s recent behavior in relation to monetary policy decisions. Since the Federal Reserve began easing interest rates on September 17, Bitcoin has retreated about 20%, while the Nasdaq has advanced 6%. The unsettling conclusion: when tech stocks fall, Bitcoin suffers even steeper declines.

Reuters reports in late November corroborated that valuations linked to AI and macroeconomic metrics like the Buffett Indicator have pushed U.S. stock valuations beyond the extremes observed during the dot-com era. Indices heavily concentrated in AI are experiencing sharp pullbacks and increasing volatility, even as narrative enthusiasm persists.

The mechanism of credit fragility

Funding for AI infrastructure has evolved into high-risk territory. Financing deals for AI-related data centers jumped from approximately $15 billion in 2024 to nearly $125 billion in 2025, driven by bond issuances, private credit, and asset-backed securities.

Analysts warn that some financing structures replicate patterns seen before the 2008 crisis, with “unproven risks” if asset holders or cash flows do not meet expectations. Central banks have escalated concerns to the level of systemic financial stability.

The Bank of England explicitly highlighted overextended valuations in AI-focused companies, warning that a severe correction could threaten broader markets through leveraged funds and private credit exposures. The European Central Bank makes a parallel observation in its Financial Stability Review: the surge in AI investment is increasingly financed through bond markets and private equity, exposing it to abrupt shifts in risk sentiment.

Oracle embodies this dilemma: its $50 billion AI data center spending plans, combined with a 45% increase in long-term debt and record credit default swap spreads, represent exactly the kind of balance sheet that alarms regulators. If the bubble bursts, these spreads widen, refinancing costs rise, and leveraged funds holding long positions in AI-themed assets are forced to deleverage.

Bitcoin occupies the extreme end of the risk spectrum in this liquidation chain.

The disproportionate sensitivity to liquidity cycles

Chinese researchers have documented a strong positive relationship between Bitcoin prices and global liquidity indices or broad monetary aggregates (M2). According to this analysis, Bitcoin functions as a “liquidity barometer”—it performs exceptionally well when liquidity is abundant and collapses when it contracts.

The mechanism is simple but relentless: if the AI bubble causes a credit crunch, the initial effect is a global risk appetite reduction and liquidity withdrawal. Bitcoin is historically one of the first assets liquidated by macro and growth funds when facing margin calls. This disproportionate sensitivity amplifies declines during credit stress.

The Oracle episode on December 11 captured this phenomenon precisely: $80 billion wiped from corporate market value directly correlated with Bitcoin breaking below $90,000 the same session, demonstrating that the transmission chain is active and real.

The policy factor: towards the next cycle

However, there is a second phase of the cycle that Bitcoin could leverage. Regulatory institutions expressing concern over AI-driven corrections also indirectly imply the likely response of central banks.

If AI markets and overleveraged credit wobble enough to threaten economic growth, central banks have historically responded with easing financial conditions. The International Monetary Fund warns in its Global Financial Stability Report that a “disorderly correction” is likely, emphasizing the need for cautious yet ultimately accommodative monetary policy to avoid amplifying shocks.

The COVID-19 precedent is instructive. After the March 2020 shock, massive quantitative easing and liquidity injections coincided with a surge in crypto market capitalization, from about $150 billion in early 2020 to nearly $3 trillion by the end of 2021.

Recent Seeking Alpha analyses comparing Bitcoin with global liquidity and dollar indices show that once easing is seriously activated and the dollar weakens, Bitcoin tends to record significant gains in subsequent quarters. Narrative rotation also matters: if AI stocks go through a classic bubble hangover with compressed multiples and political reactions to wasted capital, some of the speculative capital might rotate into Bitcoin as a bet on “alternative money” or decentralization.

Recent evidence shows capital concentrating in BTC over altcoins during stress. With liquidity contracting and volatility high, Bitcoin’s dominance has risen to around 57%, with ETFs serving as the preferred institutional channel.

The seemingly unsolvable dilemma

Bitcoin faces a structural trap: it cannot decouple from AI dynamics in the short term but depends on monetary policy responses after an AI collapse for its medium-term bullish potential.

In the immediate post-credit crisis period, Bitcoin suffers because it represents the extreme of macro risk volatility, and global liquidity contracts faster than most assets can absorb. In subsequent months, if central banks ease again and the dollar weakens, Bitcoin historically captures disproportionate gains as liquidity returns to risk assets.

The critical question for allocators is whether Bitcoin can survive the initial impact with enough integrity to benefit from the second wave. The answer depends on three factors: the severity of the AI correction, the speed of policy response, and whether institutional flows via ETFs remain under pressure.

The Oracle case was a preview: Bitcoin’s price on December 11 confirmed that the correlation is operational and the transmission is real. Later that session, Nvidia recovered 1.5% from intraday lows while Bitcoin gained over 3%, reclaiming $92,000—a reminder that the other side of the cycle also exists.

If the AI bubble fully deflates, Bitcoin takes the first hit. Whether it emerges strengthened depends entirely on central bank decisions afterward.