Dark pool trading is casting a shadow over market stability, researchers warn
The rise of private electronic markets is increasing systemic risk and making stock price crashes more likely.
The shift away from traditional public stock exchanges and into dark pools is increasing systemic risk by making stock price crashes more likely, a new study has found.
Dark pools are private electronic markets where investors can buy and sell shares without displaying their orders publicly.
While they offer lower trading costs, researchers warn that their growing use is reducing transparency and increasing the risk of sudden stock price slumps.
“A key reason uninformed trades are drawn to dark pools is the small but meaningful price advantage they offer,” said Ken Shaw, professor of accounting at the Robert J. Trulaske, Sr. College of Business and lead author of the study. “Dark pools typically have narrower bid–ask spreads, which reduces transaction costs.”
Dark pools tend to attract uninformed traders - investors trading primarily for liquidity rather than because they possess valuable private information.
Informed traders, by contrast, prefer public exchanges, where execution is more reliable and speed matters. If they believe they have an information advantage, they want their trades completed immediately before that edge disappears.
As uninformed traders migrate to dark pools, public exchanges are left with a higher concentration of informed traders. That shift makes trading on public markets riskier and more expensive, as market makers widen spreads to protect themselves.
Public markets also play a key role in corporate oversight. Informed traders scrutinise companies, question management and help force the release of both good and bad news. When trading becomes more costly and less attractive for these investors, fewer resources are devoted to uncovering firm-specific information.
As a result, negative developments can remain hidden for longer. When that information eventually becomes public, the adjustment in share prices can be sharper and more abrupt, increasing the likelihood of sudden crashes, according to Shaw and researchers at Saint Louis University.
Casting light on the systemic risk of dark pools
The study also found that companies with heavy dark pool trading were more likely to make unusual accounting adjustments in the period leading up to a crash. These adjustments can allow managers to smooth earnings or mask underlying problems, postponing the disclosure of bad news.
“This suggests accounting manipulation may be used to hoard bad news,” Shaw said. “By smoothing earnings or masking underlying economic problems, managers can temporarily sustain the appearance of strong performance.”
Shaw and his colleagues began examining dark pools after the Securities and Exchange Commission raised concerns about the risks posed by anonymous electronic trading venues, whose use has expanded significantly over the past decade. The researchers analysed FINRA data covering a large sample of companies from 2014 to 2023.
READ MORE: Machine vs machine: Defending critical financial systems in the era of Agentic AI
READ MORE: Financial tech raises systemic risk by accelerating bank runs, Bank of England warns
On traditional exchanges such as the New York Stock Exchange and NASDAQ, market makers facilitate trading by quoting bid and ask prices and standing ready to execute transactions. Dark pools operate differently: trading is fully electronic and anonymous, and execution occurs only when buy and sell orders match.
For informed traders, whose information loses value quickly, that execution risk is costly. As a result, they are more likely to favour organised exchanges, where trades are completed more reliably.
“When it becomes harder and more expensive to profit from private information, traders have less incentive to acquire it in the first place,” Shaw said. “As a result, less effort is devoted to uncovering firm-specific information.”
The paper, Crashing in the Dark? Trading and Stock Price Crashes, was published in the Journal of Business Finance & Accounting. Co-authors are Bidisha Chakrabarty and Xu (Frank) Wang of Saint Louis University.
