Stock Market Crash of 1987

What Was the Stock Market Crash of 1987?

The stock market crash of 1987 was a rapid and severe downturn in U.S. stock prices that occurred over several days in late October 1987. While the crash originated in the U.S., the event impacted every other major stock market in the world.

In the five years leading up to the 1987 crash, the Dow Jones Industrial Average (DJIA) had more than tripled. On October 19, 1987 — known as Black Monday — the DJIA fell by 508 points, or by 22.6%. Up to this point in history, this was the largest percentage drop in one day. The crash sparked fears of extended economic instability around the world.

After this crash, the Federal Reserve and stock exchanges intervened by installing mechanisms called "circuit breakers," designed to slow down future plunges and stop trading when stocks fall too far or too fast.

Understanding the Stock Market Crash of 1987

After five days of intensifying declines in the stock market, selling pressure hit a peak on October 19, 1987, also known as Black Monday. Steep price declines were created as a result of significant selling; total trading volume was so large that the computerized trading systems could not process them. Some orders were left unfilled for over an hour, and these order imbalances prevented investors from discovering the true price of stocks.

Heightened hostilities in the Persian Gulf, a fear of higher interest rates, a five-year bull market without a significant correction, and the introduction of computerized trading have all been named as potential causes of the crash. There were also deeper economic factors that may have been to blame.

Under the Plaza Accord of 1985, the Federal Reserve made an agreement with the central banks of the G-5 nations — France, Germany, the United Kingdom, and Japan — to depreciate the U.S. dollar in international currency markets in order to control mounting U.S. trade deficits. By early 1987, that goal had been achieved; the gap between U.S. exports and imports had flattened out, which helped U.S. exporters and contributed to the U.S. stock market boom of the mid-1980s. 

In the five years preceding October 1987, the DJIA more than tripled in value, creating excessive valuation levels and an overvalued stock market. The Plaza Accord was replaced by the Louvre Accord in February 1987. Under the Louvre Accord, the G-5 nations agreed to stabilize exchange rates around this new balance of trade.

In the U.S., the Federal Reserve tightened monetary policy under the new Louvre Accord to halt the downward pressure on the dollar in the time period leading up to the crash. As a result of this contractionary monetary policy, growth in the U.S. money supply plummeted from January to September, interest rates rose, and stock prices began to fall by the end of the third quarter of 1987. 

The Role of Program Trading and Automation

The stock market crash of 1987 revealed the role of financial and technological innovation in increased market volatility. In automatic trading, also called program trading, human decision-making is taken out of the equation, and buy or sell orders are generated automatically based on the price levels of benchmark indexes or specific stocks. Leading up to the crash, the models in use tended to produce strong positive feedback, generating more buy orders when prices were rising and more sell orders when prices began to fall.

After the crash, exchanges implemented circuit breaker rules and other precautions that slow down the impact of trading irregularities. This allows markets more time to correct similar problems in the future. For example, if stocks dove by even 7% today, trading would be suspended for 15 minutes.

While program trading explains some of the characteristic steepness of the crash (and the excessive rise in prices during the preceding boom), the vast majority of trades at the time of the crash were still executed through a slow process, often requiring multiple telephone calls and interactions between humans.

With the increased computerization of the markets today, including the advent of high-frequency trading (HFT), trades are often processed in milliseconds. As a result of incredibly rapid feedback loops among the algorithms, selling pressure can mount within moments, and huge losses can be experienced in the process.