Black Monday 1987: Could 11,000-Point Drop Happen Today?

On October 19, 1987, the Dow Jones Industrial Average experienced one of the most dramatic single-day collapses in market history, plunging 508 points—a staggering 22.6% decline—from 2,246.74 to 1,738.74. The carnage actually began the previous Friday with a 5% drop, creating what one observer described as ‘terrific anxiety’ over the weekend. When measured against today’s market levels, that 508-point collapse would translate to nearly 11,000 points, a scale of loss that would dwarf even the 2008 financial crisis.

The pre-crash environment in 1987 bears striking similarities to current conditions. According to the analysis from 24/7 Wall St., the Dow had surged 67% from January 1985 to mid-1987, creating significant overvaluation concerns. Today, the market has seen a 57% gain over the most recent three years, approaching the rapid appreciation that preceded the 1987 crash. Interest rates were rising then, just as they are today, and Congress was debating tax treatment of M&A activity, mirroring current regulatory uncertainties.

Famed economist Robert Shiller, cited in the original text, believed the 1987 crash was ‘as much a sociological or psychological phenomenon as an economic one.’ This psychological dimension remains relevant today, as market sentiment can shift rapidly when valuations appear stretched and investors grow nervous about concentrated risks in specific sectors or companies.

While the Dow Jones Industrial Average served as the primary benchmark in 1987, today the S&P 500 provides a more comprehensive market picture—and it reveals a concerning concentration of value. The so-called Magnificent 7 stocks—Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia, and Tesla—now constitute 34% of the entire S&P 500 index value. This extreme concentration creates systemic risk reminiscent of the narrow market leadership that preceded previous crashes.

Early cracks are already appearing in this foundation. Apple Inc. (NASDAQ: AAPL) has gained only 2% this year, significantly underperforming the broader market. The primary reason, according to the source analysis, is Apple’s lack of a high-end artificial intelligence product while AI-focused companies see their valuations soar. Similarly, Tesla Inc. (NASDAQ: TSLA) has managed only a 9% gain this year, hampered by questions about whether it’s primarily a car company or an AI and robotics operation, compounded by the political leanings of CEO Elon Musk.

The core valuation premise for the world’s most valuable stocks now hinges almost entirely on the future of artificial intelligence. Nvidia, Microsoft, Meta, Amazon, and Alphabet have all committed to spending tens of billions of dollars on AI data centers this year and next. Their earnings trajectories depend entirely on whether their massive AI bets prove correct—creating a make-or-break scenario for nearly one-third of the entire S&P 500.

The fundamental question driving today’s market valuation, according to the source analysis, is whether AI will become a product people willingly pay for or one that’s given away almost entirely for free. This distinction will determine whether the tens of billions being invested in AI infrastructure generate substantial returns or become commoditized offerings with minimal profitability.

The upcoming third-quarter earnings season will provide critical early answers about AI’s commercial viability. If companies like Nvidia, Microsoft, and Meta Platforms deliver shaky results or cautious forecasts regarding their AI investments, the market could experience a significant downward adjustment—potentially of staggering proportions given the concentrated nature of current market leadership.

Just as concerns about U.S. trade deficits and rising interest rates contributed to the 1987 crash environment, today’s market faces its own set of macroeconomic headwinds. However, the unique risk lies in the technological bet that has come to dominate market valuations. The AI revolution either validates current price levels or exposes them as dangerously overextended, with little middle ground given the scale of investment and expectations.