The “Incomplete Revelation Hypothesis” and Financial Reporting

INTRODUCTION The most common form of the Efficient Markets Hypothesis (EMH) states that market prices fully reflect all publicly available information (Fama 1970). The EMH has been highly influential among academics, but practitioners and regulators appear unconvinced. Investors work hard to identify mispriced stocks on the basis of public data, or pay others to do so, even though the EMH asserts that such efforts are wasted. Managers seek to boost stock prices by hiding bad news in footnotes, and regulators work hard to defeat such efforts, even though the EMH asserts that information is reflected in prices no matter how obscure its presentation. Beliefs about inefficiency play a central role in the debate over recognizing expenses for incentive stock options. Opponents of expensing argue that the resulting lower net income will inappropriately reduce market prices, while proponents argue the market does not fully recognize compensation costs reported only in footnotes. In efficient markets, however, expensing these costs has no direct effect on prices, as long as the details of the compensation are included in footnotes. The decision to expense option costs could reduce stock price indirectly, even in efficient markets, by affecting the terms of contracts between the reporting firm and other parties (Watts and Zimmerman 1986). However, few of the parties to the debate appear concerned about these effects. The academic community is showing increasing dissatisfaction with the EMH, swayed partly by evidence that prices underreact to large earnings changes, ratios of prices to fundamentals, and other statistics derived from fundamental accounting analyses. However, the EMH is still influential because there is no alternative theory that explains why we observe the inefficiencies we do. For example, why should the market underreact to large earnings changes, rather than overreact? Without a theory predicting how and why markets are inefficient, studies showing mispricing can be viewed as statistical flukes resulting from fishing expeditions (Fama 1998; Kothari 2001). In this paper, I present an alternative to the EMH called the "Incomplete Revelation Hypothesis" (IRH). The IRH asserts that statistics that are more costly to extract from public data are less completely revealed in market prices. The IRH can account for many of the phenomena that are central to financial reporting but inconsistent with the EMH. It predicts that investors devote substantial resources to identifying mispriced stocks on the basis of public data, that managers seek to boost stock prices by hiding bad news in footnotes, and that regulators may wish to defeat such efforts, because information that is hard to extract from financial statements will not be reflected in stock prices. The IRH also provides a number of novel and testable predictions that distinguish it from the EMH. THE INCOMPLETE REVELATION HYPOTHESIS The IRH is based on equilibrium outcomes in "noisy rational expectations" models. (1) In these models, rational agents choose whether to collect information about the value of an asset. Those who choose to collect the information then trade the asset in a market that also includes "noise" traders. Noise traders are so named because they trade randomly, in response to liquidity shocks, portfolio rebalancing needs, or even irrational whims. This noise keeps prices in the market from revealing information completely, because traders who observe only price cannot tell whether prices are high because informed traders have good news, or because noise traders happen to be buying heavily. This uncertainty allows the informed traders to profit from their information advantage. A key result of noisy rational expectation models is that there is an equilibrium in which just enough traders collect information to make their trading gains equal to their collection costs. …