No news is bad news? evidence from security analysts' earnings forecasts

Abstract

This thesis documents the systematic skipping of earning forecast by security analysts and investigates the relationship between the absence of news and the performance of related firms. We find that these skipping are associated with negative information about the stocks, and are not immediately recognized by the market. A long-short trading strategy that utilizes forecast skipping generates significant abnormal return. We argue that when facing negative information about the covered firm, some analysts choose to keep silent instead of lower their forecast. We also provide an alternative way to capture the effect of analysts' silence. The average factor-adjusted return of firms in the longest silent time quintile is significantly lower than that of firms in other quintile. And this effect is stronger in the months when analysts issue earnings forecasts more frequently. These results also provide some insights for investors when analyzing security analysts' earnings forecasts.

Date of Award	2015
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology