What ‘Black Monday’ fears really mean for AI stocks and crypto

Over the weekend, timelines were suddenly flooded with warnings about a looming “Black Monday” – comparisons to the infamous 1987 crash, charts of plunging AI stocks, and calls for a brutal open in traditional markets. If you’re a crypto investor, it’s natural to wonder whether this is just noise or a real threat – and whether there’s an opportunity hiding underneath the fear.

Why everyone is suddenly talking about Black Monday

The original Black Monday happened on 19 October 1987, when the Dow Jones fell 22.6% in a single day and the NASDAQ dropped over 11%. Whenever markets get shaky, people love to recycle that label for dramatic effect.

This time, the “new Black Monday” chatter didn’t start on Wall Street – it started in crypto. Over the weekend, tokenized versions of major tech and AI-related stocks listed on crypto exchanges began to drop several percent while the traditional stock market was closed. That weekend price action lit up social media with predictions of a brutal Monday open.

How tokenized stocks on crypto exchanges sparked the panic

Traditional stock markets close on weekends, but crypto trades 24/7. Thanks to tokenized and synthetic products, you can now trade “stocks” like SanDisk, Micron, or Coreweave on decentralized exchanges (DEXes) and some centralized crypto platforms even when Wall Street is shut.

Here’s what happened over this particular weekend:

• SanDisk closed around $12.99 on Friday in traditional markets, but its tokenized version was quoted near $12.58 on crypto – roughly a 3% drop.

• Micron closed near $8.78, but traded around $8.60 on-chain – about 2% lower.

• Coreweave, a key AI data center play, traded around $60 on crypto, roughly 2.5% below its Friday close near $61.39.

For big, liquid tech names, a 2–5% gap over a quiet weekend is a big move. For traders used to traditional hours and lower volatility, seeing these drops on Binance, Hyperliquid, and other venues looked like the start of a crash in real time – even though the actual stock market was still closed.

In other words, crypto’s 24/7 markets became a live, high-volatility preview of how AI and tech stocks might open on Monday. That preview is what fueled the “Black Monday” narrative.

The real problem: an AI infrastructure slowdown

Underneath the weekend drama, there is a genuine issue developing in AI-related stocks – particularly the companies building out AI infrastructure. While headline indices like the NASDAQ are only about 7% off all-time highs, the pain under the surface is much worse in certain sectors.

Many of the stocks getting hit hardest are those tied to the AI buildout:

• Coreweave – a major AI data center and GPU infrastructure provider – is down around 68% from its peak.

• Nebius is down roughly 45% from its high.

• Oracle, which leaned heavily into data center and cloud investment, is down more than 60% from its peak.

These are not speculative meme names – they are core players in building the hardware, energy, and data center backbone of AI. Their sharp drawdowns are a sign that the AI buildout is hitting a funding wall.

Why rising interest rates are crushing AI builders

The root cause is simple: debt is getting more expensive.

The yield on the US 10-year Treasury moved from around 4% to near 5% this year. That might sound like a small shift, but in percentage terms it means the US government is paying roughly 25–30% more to borrow compared to earlier in the year.

Because government bonds are treated as the “risk-free” benchmark, higher yields there ripple through the entire credit market. If the risk-free rate rises, every riskier borrower – including AI infrastructure companies – must pay even more to attract lenders.

For AI builders, this is a major problem. Their business model is capital-intensive: they need to finance GPUs, data centers, power contracts, and networking gear up front, often using long-term debt. As rates climb, the cost of financing each new “box” of infrastructure explodes.

Inside the AI ‘box’ financing model

To understand why markets are nervous, it helps to look at how companies like Coreweave structure their financing.

In simplified form, the model looks like this:

• The company signs a long-term contract with a big customer (for example, Microsoft) to provide a certain amount of compute over several years at a fixed price.

• They bundle that contract into a special-purpose vehicle – often described as a “box” – and add all the related costs: GPUs, data center leases, power, and so on.

• They then borrow money against this box from lenders, using the contracted revenue as collateral.

• Cash flows from the customer are used to pay operating costs, interest, and principal on the debt. Anything left over flows back to the company as profit.

The advantage of this setup is that each box is ring-fenced. If one box underperforms, it doesn’t automatically drag down all the others. In theory, that should limit contagion risk.

But there are two big catches:

• The contracts are often fixed-price. If spot demand for compute explodes and prices rise, the company doesn’t fully benefit because they’ve pre-sold capacity at a locked-in rate.

• They still need to raise huge amounts of new debt. In Coreweave’s case, the company reportedly already has around $35 billion in debt tied to these boxes and may need another $35 billion to fully finance all existing contracts.

When interest rates were low, this structure looked brilliant: predictable revenue, cheap borrowing, and massive AI demand. As rates climb, the math gets much tighter – and markets are starting to price in that risk.

Credit default swaps and default risk in AI names

One of the clearest warning signs is in the credit derivatives market, specifically credit default swaps (CDS). A CDS is essentially insurance that pays out if a borrower defaults on their bonds. The higher the CDS spread, the higher the perceived risk of default.

For companies like Coreweave and other AI hyperscalers, CDS spreads have spiked. In one example, default insurance implied:

• About a 16% chance of default per year.

• Roughly a 55% chance of default over five years – essentially a coin flip over that horizon.

At the same time, yields on their existing bonds have blown out. Coreweave issued a bond with a coupon near 9.75%; the market now prices that bond closer to a 15% yield. That doesn’t change what existing holders receive, but it signals that new buyers demand far higher compensation to hold the risk.

Put simply, the smartest credit investors in the room are saying: these AI builders are getting dangerously close to the edge if rates stay high and funding needs remain massive.

How this feeds into wider market stress

This AI funding squeeze is one of the reasons the NASDAQ had such a rough week, dropping more than 6%. While mega-cap names like Nvidia and Amazon haven’t collapsed, the broad AI infrastructure complex has been hammered, and that weakness is finally showing up in the indices.

Other fear gauges confirm the stress:

• The stock market fear and greed index has sunk into extreme fear territory, around 18.

• The VIX, Wall Street’s volatility index, spiked above 22 before easing back toward 20.

• Goldman Sachs’ “panic index” jumped to more than a three-standard-deviation move on Friday – a sign of a very nervous market.

Layer on top of this the macro backdrop – persistent inflation pressures, geopolitical shocks like the Iran war, and a bond market demanding higher yields – and you can see why traders are on edge heading into Monday opens.

Is a 1987-style Black Monday likely?

Despite the scary headlines, a repeat of 1987’s one-day 20% wipeout is not the base case.

Several things can be true at once:

• Tech and AI stocks can continue to correct. The NASDAQ is only about 7% off its highs, so more downside is very possible, especially if funding conditions for AI builders keep tightening.

• We can see a sharp down day (or several) without a historic crash. Markets can grind lower, chop sideways, or stage brief relief rallies even in the middle of a broader de-risking phase.

• Crypto doesn’t have to follow stocks tick-for-tick. Earlier in the AI mania, capital rotated out of crypto into high-flying AI names. Now that the AI trade is cooling, that pressure on crypto may ease over time.

The important takeaway is that the current stress is less about an overnight apocalypse and more about a medium-term adjustment: the AI bubble is slowing, leverage is being repriced, and capital-intensive growth stories are being forced to live with higher rates.

How the bond market is doing the Fed’s job

Interestingly, just as equities started wobbling, long-term yields began to pull back. The 10-year and 30-year US Treasury yields dipped as stocks sold off, suggesting that the bond market sees its own tightening as starting to bite.

That’s how the system is supposed to work:

• Higher yields make borrowing more expensive.

• Expensive borrowing slows capital-intensive projects like AI data centers.

• Slower AI buildout reduces demand for energy, construction, and high-end chips, easing some inflation pressures.

• As inflation expectations cool, long-term yields can stabilize or drift lower – even without new rate hikes from the Fed.

In effect, the bond market is tightening financial conditions on its own, which may reduce the need for the central bank to push policy rates much higher. That’s painful for AI infrastructure names right now, but it’s also how excesses get wrung out of a hot sector.

Why cheaper, more efficient AI is a long-term positive

Amid all the fear, there’s a quieter but important trend: AI itself is getting more efficient and cheaper to run. Models like DeepSeek are targeting significantly lower costs per thousand calls compared to offerings from OpenAI, Anthropic, or xAI’s Grok.

That’s exactly what you’d expect in a maturing tech cycle:

• Early phases are expensive, capital-hungry, and dominated by infrastructure buildout.

• Competition and innovation push costs down, making the technology more accessible and broadening real-world adoption.

Think of the progression from dial-up internet to broadband to fiber. Each step made the underlying tech cheaper and better, even if infrastructure investors had to endure painful cycles along the way. In the long run, more efficient AI is a net positive for the broader economy – and ultimately for crypto, which thrives in a more digital, automated world.

What this AI unwind means for crypto

During the peak of the AI trade, capital flooded into names like Coreweave, SanDisk, and other AI-linked plays. Some of that money came directly out of other risk assets: property, traditional tech, and yes, crypto.

Now, several things are happening at once:

• The AI mania is cooling. Returns in the sector are no longer one-way up, and funding is getting harder.

• Crypto has been relatively stable during the latest AI wobble. While stocks have been sliding, major crypto assets haven’t shown the same level of panic selling.

• Macro uncertainty remains high. That can cap upside in both stocks and crypto in the short term, but it also keeps alternative assets in the conversation.

For crypto investors, the key is to understand that this is a rotation story as much as it is a risk-off story. When AI was the only game in town, it drew capital away from other sectors. As that trade normalizes, capital can start to look elsewhere again – including back into digital assets, especially if they show signs of bottoming. For example, some analysts are already debating whether current price action in majors like Bitcoin and XRP represents a final shakeout before a larger adoption wave, as discussed in pieces like this deep dive on whether XRP is really going under $1.

Using 24/7 crypto markets to trade traditional risk

One unique angle for crypto-native traders is the ability to express views on traditional assets even when their home markets are closed.

On DEXes like Hyperliquid and similar platforms, you can:

• Trade tokenized versions of stocks such as SanDisk, Micron, and Coreweave.

• Take long or short positions on major indices like the S&P 500 via perpetual contracts.

• Use leverage (often up to 10x or more) – though this dramatically increases risk and is not suitable for most investors.

This means that if you have a strong view about whether Monday will be a “Black Monday” or just another volatile open, you can position over the weekend. For example:

• If you expect a sharp gap down in AI names, you might short tokenized Coreweave or SanDisk on a DEX.

• If you think the weekend fear is overblown and markets will bounce, you might go long the same names or indices instead.

However, this isn’t a free lunch. Weekend order books are often thinner, slippage can be higher, and leverage can wipe you out quickly if you’re wrong. Treat these tools as high-risk instruments, not as a guaranteed way to front-run Monday’s open.

Risk management for crypto investors in this environment

Whether or not we get a dramatic Monday, the bigger takeaway for crypto investors is how to navigate a world where AI, rates, and macro are tightly intertwined.

Consider a few practical guidelines:

• Expect higher volatility across risk assets. AI stocks, tech, and crypto are all sensitive to rates and liquidity. Sudden moves in bond yields or inflation data can trigger sharp swings.

• Be cautious with leverage. Leveraged trades on AI-linked perps or indices can move in your favor quickly – but they can also liquidate you in a single spike. Size positions so that a wrong call doesn’t blow up your portfolio.

• Watch the bond market, not just crypto charts. The 10-year and 30-year yields, credit spreads, and CDS pricing on big AI names are telling you where stress is building. They often move before equities and crypto react.

• Think in terms of cycles, not days. The AI buildout isn’t over; it’s entering a more mature, cost-conscious phase. Crypto’s own cycles – including major regulatory milestones and adoption trends – will play out over months and years, not just one Monday.

If you’re trying to understand where we are in the broader crypto cycle, it’s worth pairing this macro view with focused analysis on key assets. For instance, articles like this in-depth discussion on where Bitcoin stands now can help you frame long-term positioning beyond short-term AI volatility.

The bottom line: fear, opportunity, and perspective

The “Black Monday” buzz is a mix of real stress and social media drama. Yes, AI infrastructure stocks are under pressure, credit markets are flashing warning signs, and higher rates are forcing a reset in some of the most hyped corners of the market.

But a historic one-day crash is not inevitable. What’s more likely is an ongoing repricing of growth stories that relied on cheap debt – and a gradual cooling of the AI bubble that previously sucked liquidity out of everything else, including crypto.

For crypto investors, this is a time to stay informed, watch the bond market, and be selective rather than reactive. Use crypto’s 24/7 tools wisely, manage risk tightly, and keep your focus on the bigger picture: how AI, macro, and digital assets fit together in the next phase of this cycle, not just how scary one Monday might look on your feed.