The Value of Information: A Puzzle

2026-05-11

AI Summary

This study addresses the puzzle of why the true value of information to informed traders in financial markets is substantially lower than the costs investors incur to acquire it. Drawing on market microstructure theory, we propose the covariance between price changes and order flow as a direct measure of the total value of information—an estimate that, under competitive market-making conditions, equals the profits earned by informed traders. Using high-frequency data from U.S. equities, we empirically estimate that the annual value of information for an individual stock averages approximately $3.5 million, or just 0.04% of its market capitalization. This figure stands in stark contrast to the 0.67% annual information-gathering cost reported by French (2008), revealing a pronounced disparity between the economic value of private information and the resources devoted to obtaining it—the so-called “information value puzzle.”

Abstract

We show that under mild assumptions, the total value of information to informed traders in the market can be measured by the covariance between price changes and order flow. This covariance captures noise trader losses, which equal informed trader gains when market making is competitive. We estimate the value of information using high frequency data on US equities at about $3.5 million per year for the average stock. The aggregate value of information is about 0.04% of market cap, which is considerably lower than the 0.67% in fees investors pay each year searching for superior returns (French 2008). We discuss potential resolutions for these puzzling findings.

Problem

• value of information
• informed traders
• noise trader losses
• market efficiency
• information asymmetry

Innovation

• value of information
• covariance
• order flow
• informed trading
• noise traders