Could Algorithmic Trading Trigger a Market Crash Larger Than 1987?

Amidst the excitement of reaching new market peaks, there’s an underlying concern that stock markets might face a more rapid and intense crash than the infamous 1987 downturn. The surge in algorithmic trading—where computers execute trades based on pre-set rules—has amplified this risk, according to recent insights from Barron's. Increasingly, vast sums are managed by algorithms that select stocks, execute trades, manage risk, and capitalize on market volatility. Investors with a keen memory will recall that program trading played a significant role in the 1987 crash, although automated strategies were far less prevalent at that time. (For further reading, see: The Advantages and Disadvantages of Automated Trading Systems.)

Massive Yet Vulnerable

Quantitative trading strategies driven by computers controlled approximately $933 billion in hedge fund assets by mid-2023, marking an 87% increase from $499 billion in 2007, based on Hedge Fund Research Inc. (HFR) data cited by Barron's. Additionally, computer-based index ETFs represent around $3 trillion in investments.

Recent history has witnessed sudden, sharp declines in asset prices. Barron's cautions that the next significant market selloff could be exacerbated by the lightning-fast reactions of computerized trading systems, which now play a dominant role in market dynamics. "The financial system is more fragile than many realize," warns Michael Shaoul, Ph.D., CEO of Marketfield Asset Management LLC.

Dangerous Feedback Loops

On Black Monday, October 19, 1987, the Dow Jones Industrial Average plunged 508 points, a staggering 22.6% drop. Similarly, during the May 6, 2010 flash crash, the Dow tumbled about 9% and the S&P 500 dropped roughly 7% within minutes before rebounding. Another flash crash occurred on August 24, 2015, with the S&P 500 falling 5% shortly after the opening bell, and the Dow losing 1,100 points (approximately 6.7%) in the first five minutes, as reported by CNBC. (See also: The Two Most Significant Flash Crashes of 2015.)

Back in 1987, program trading triggered a "toxic feedback loop," where automated sell orders drove prices down, initiating further selling by these systems. Similar patterns were observed during the August 2007 "Quant Quake," which caused the S&P 500 to drop 3.3%, and the August 2015 flash crash, both involving cascading sell-offs fueled by computerized trading algorithms.

Complex Algorithms, Critical Flaws

Even highly intelligent professionals can develop flawed trading algorithms or quantitative funds. Long-Term Capital Management LP (LTCM), a hedge fund employing quantitative methods and featuring two Nobel Prize-winning partners, nearly collapsed the broader market in 1998 due to its risky, highly leveraged strategies. The Federal Reserve had to intervene with a bailout to stabilize the situation, as noted by Barron's.

The Perils of Speed

Unlike the 1987 crash, where program trading was significant but trading processes were slow and involved human interaction, today’s markets operate at lightning speed thanks to high-frequency trading (HFT). Trades are executed within milliseconds, enabling rapid feedback loops among algorithms. This speed can quickly escalate selling pressure into a market tsunami, erasing wealth in moments. Prepare for volatility like never before.

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