Sp. Bandyopadhyay et al., ANALYSTS USE OF EARNINGS FORECASTS IN PREDICTING STOCK RETURNS - FORECAST HORIZON EFFECTS, International journal of forecasting, 11(3), 1995, pp. 429-445
Little attention has been paid to a principal decision context in whic
h analysts' earnings forecasts are prepared, namely, as an input to th
eir recommendations. We use two data sets, Value Line, USA, and Resear
ch Evaluation Service, Canada, and examine the importance of analysts'
earnings forecasts for their stock price forecasts via three hypothes
es: (1) analysts' earnings forecasts are important for their stock pri
ce forecasts; (2) analysts' long-term earnings forecasts are more impo
rtant than their short-term earnings forecasts for their predictions o
f stock prices over a particular stock price forecast horizon; (3) the
importance of analysts' earnings forecasts for their stock price fore
casts rises as the joint earnings and stock price forecast horizon inc
reases. We show that: (1) when the earnings forecast horizon is the ne
xt fiscal year, forecasted earnings explain only 30% of the variation
in forecasted price; (2) the importance of forecasted earnings for for
ecasted price rises as the earnings forecast horizon increases; (3) in
the long run, (i.e. three to five years hence), forecasted earnings e
xplain about 60% of the variation in forecasted price. Decision useful
ness is an ex ante concept, but tests regarding the usefulness of earn
ings for stock price generally have used actual (not expectational) da
ta. Our evidence suggests that earnings expectations are decision usef
ul, where the decision context is sell-side analysts' stock price fore
casts. Our results are potentially important to users of sell-side ana
lyst research reports. When a stock recommendation is accompanied only
by short-run earnings forecasts, investors need to closely examine es
timates of non-earnings variables to assess the quality of stock recom
mendations. In contrast, when stock recommendations are accompanied by
both short-run and long-run earnings forecasts, investors need to exa
mine estimates of non-earnings information variables less closely.