Fair value intensity and analyst forecasts

Abstract

Analysts’ earnings and book value forecasts play an important role in price discovery in equity markets. As the role of fair value measurements in accounting increases, the impact on analysts’ ability to accurately forecast earnings and book values is unclear. This article develops a method to calculate the degree of fair value measurement in financial statements and investigates the impact thereof on the accuracy of analysts’ book value and earnings forecasts, using a sample of firms listed in the United States and the United Kingdom from 2010 to 2014. Relying on multivariate regression findings, the article shows that greater fair value intensity decreases the 12-month analyst forecast accuracy for earnings in both countries. Moreover, there is some evidence that higher fair value intensity decreases the accuracy of analysts’ book value forecasts. It therefore appears that increased fair value intensity under a mixed measurement approach limits the ability of analysts to forecast earnings, without a compensating impact on forecasts of book values.

Keywords

• Accuracy
• Analyst
• Book Value
• Earnings
• Fair Value
• Forecast