Abstract:
This study examines whether analysts' recommendations can predict stock price
crashes, and whether this predictability is different during good and bad
macroeconomic periods. Recent literature suggests that investors rely on analysts
during bad times, when there more is a larger degree of uncertainty. We examine
analysts' consensus recommendation changes prior to stock price crashes in
recessionary economic conditions and in normal conditions. We examine a sample
of 11,903 observations in the US stock market, from 1995 to 2013, collected from
the Institutional Broker Estimation System (IBES) database. We employ a cross
sectional regression methodology for this study. Using two different proxies of
stock price crash, we find that analysts' downgrades are followed by a larger
possibility of a crash in normal macro conditions, and a smaller possibility of a
crash in unfavourable periods. Vffe use four different definitions for good and bad
macroeconomic conditions. We find statistically significant evidence to suggest
that analysts' recommendations are able to predict crashes m norma
macroeconomic conditions, however we do not find empirical evidence for this
notion during bad macroeconomic conditions.
