The Impact of Algorithmic Trading on Intensifying Stock Market Downturns

While self-driving cars are celebrated as breakthroughs enhancing road safety, algorithmic trading in the stock market is drawing criticism for its role in amplifying sharp price declines and heightened volatility.

Todd Rosenbluth, director of ETF and mutual fund research at CFRA, explained to Barron's that "rules-based strategies remove emotional bias, which can lead to intensified selling during downturns and increased buying during upswings."

On Friday's market open, the S&P 500 Index (SPX) rose 0.81% from Thursday's close, inching up to 0.85% by 10:15 AM New York time.

Accelerated Herd Mentality

As Rosenbluth noted, algorithmic or program trading can trigger rapid, self-reinforcing market trends that outpace human reaction times. Many algorithms are designed to follow momentum, and the recent stock price correction worsened as these systems abruptly switched from buying to selling.

Keith Lerner, chief market strategist at SunTrust Private Wealth Management, described the market action to Barron's as "abnormal, like a rubber band snapping." Momentum investing fueled the market's swift ascent, while now intensified selling pressure is accelerating declines.

Washington Post columnist Steven Pearlstein remarked, "The market behaves irrationally and detached from fundamentals both on the rise and fall, a phenomenon intensified today by computerized high-frequency trading. This week’s activity exemplifies herd behavior on steroids."

A Dangerous Feedback Cycle

The issue is compounded because many trading firms develop algorithms following similar decision-making rules. The infamous 1987 Black Monday crash, where the Dow Jones Industrial Average plunged 22.6%, was driven by a "toxic feedback loop" among these programs, according to previous Barron's reports.

Since then, algorithmic trading has grown significantly, controlling a larger share of market transactions and increasing systemic risks. (See also: Could Algorithmic Trading Trigger a Crash Worse Than 1987?)

Algorithmic Dominance

A recent analysis revealed that by 2016, trading algorithms managed nearly $8.8 trillion in financial assets globally, with projections estimating growth to $18.2 trillion by 2025 at an annual rate of 8.7%, as reported by Business Wire.

Data from JPMorgan Chase & Co. indicates that quantitative and passive investment strategies now represent about 60% of all equity assets, doubling over the past decade, according to Bloomberg. Conversely, individual human investors and discretionary managers account for only roughly 10% of equity trading volume. Passive investments include index funds structured as mutual funds or ETFs.

Supporters’ Perspective

Proponents of automated trading emphasize benefits such as consistency, discipline, emotional detachment, and rigorous analysis. They argue these systems introduce greater logic into trading and investing, enabling market prices to rapidly reflect shifting fundamentals or perceptions.

Additionally, following the 1987 crash, major exchanges like the New York Stock Exchange (NYSE) have implemented circuit breakers—temporary trading halts during steep selloffs—to prevent panic and allow market participants to reassess. (See also: The Advantages and Disadvantages of Automated Trading Systems.)

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