A Bayesian Understanding of Information Uncertainty and the Cost of Capital

Abstract

The term "information risk" or "information uncertainty" is defined as the risk of a misleading signal. This risk is understood Bayesianly in terms of the likelihood function f(S|φ). In Bayesian method, f(S|φ) captures the quality of signal S with respect to parameter φ. The Bayesian position is that even a highly informative signal (one with a very peaked likelihood function) can bring an increase in uncertainty, and hence an increase in the cost of capital. It can also occur that the cost of capital implied by a capital asset pricing model (CAPM) increases even when better information brings greater certainty. The role of financial reporting should be understood not in terms of its effect on the cost of capital per se, but as aiding investors to assess the probability distributions of future cash flows more accurately, thereby leading on average to higher expected utility portfolios. This is a technical version of the traditional view in accounting theory that financial disclosure should provide generally relevant information for asset valuation and other investment decisions.

Keywords: Information uncertainty, information risk, cost of capital, accounting information, log CAPM

JEL Classification: D80, D83, G10, G14, C11