The department of finance’s Ahmed Baig has had his paper “Price clustering and the informational efficiency of stock prices” published in the Journal of Financial Research.
The paper focuses on “price clustering,” a common pattern where stock prices land on a clean number, like $15 instead of $15.07. Baig aimed to explore how settling on round numbers instead of precise ones, affects the market. Baig analyzed broad market data and found a clear trend: stocks that clustered more were also the ones whose prices did a poorer job of tracking true market information.
The finest example of this came from a natural experiment in 2016, when the U.S. Securities and Exchange Commission temporarily forced certain stocks to trade in larger price steps. That policy created more clustering. The result? Those stocks became noticeably less efficient, bouncing back only once the policy ended.
The key takeaway from Baig’s work is when stock prices get too “rounded,” the market loses some of its power to process and signal real information, showing that even the slightest misinformation can have big effects.