The dispersion31 or volatility of analysts’ earnings forecasts is used to study the level of
uncertainty in earnings forecast decision making and whether it affects firm attributes in capital markets such as trading volume, risk, price movements and returns volatility. In particular, the dispersion of analysts’ earnings forecasts sourced from IBES has been used to proxy for the degree of risk, informational uncertainty and informational asymmetry in analysts’ earnings forecast dispersion research.
Earnings forecast dispersion has been used to examine the differences in analysts’ opinion: on trading volume (Ajinkya et al., 1991); on future stock returns (Baik and Park, 2003; Barron and Stuerke, 1998; Barry and Jennings, 1992; Christensen, Gaver and Stuerke, 2005; Diether, Malloy and Scherbina, 2002; Doukas, Kim and Pantzalis, 2004; Han and Manry, 2000; Johnson, 2004; Peterson and Peterson, 1982); on stock price volatility (Athanassakos and Kalimipalli, 2003; Lobo and Tung, 2000); through time (Ciccone and Etebari, 2004); and on a per period basis (Kwon, 2002). Each of these studies is reviewed in 2.8.2. The rationale underlying the literature review of the dispersion of analysts’ earnings forecasts is examined next.
2.8.1 Dispersion of Analysts’ Earnings Forecasts in Relation to Thesis Aims The rationale behind the review of the literature surrounding the dispersion of analysts’ earnings forecasts published by IBES is similar to the reasons underlying the literature review of other properties of analysts’ earnings forecasts. The rationale is detailed in 2.3.
31 Elliott and Philbrick (1990) and Swaminathan (1991) defined analysts’ earnings forecast dispersion
as:
/
it it it
FD
SD FEPS
where SDit = standard deviation of financial analysts’ forecasts (number of analysts > 2) for firm i in
year t; and
2.8.2 Literature Review of Dispersion of Analysts’ Earnings Forecasts
Dispersion of analysts’ earnings forecasts include Ajinkya et al. (1991), who found a positive relation between stock trading volume and the dispersion of IBES monthly analysts’ forecasts of annual actual earnings from 1987 through 1981 on 420 US firms. The suggested explanation for this result is that differences in analysts’ beliefs on future earnings outcomes increase the segmentation of investment strategies carried out by investors, exacerbating trade intensity.
Studies have also focused on the role of analysts’ earnings forecast dispersion as a determinant of future stock returns, which is generally measured by cumulative CARs. Empirical results presented mixed conclusions. Baik and Park (2003), Johnson (2004), Diether et al. (2002) and Han and Manry (2000) found a negative relation between analysts’ earnings forecast dispersion and future stock returns. The explanation offered by both Baik and Park (2003) and Johnson (2004) was that investors viewed information heterogeneity as an increase in uncertainty (risk) of asset values, which in turn lowered stock prices by the amount of equity return required to compensate for the increased risk.
On the contrary, Barron and Stuerke (1998), Christensen et al. (2005) and Doukas et al. (2004) found a positive price reaction (proxied by CAR) to forecast dispersion around subsequent earnings release. Doukas et al. (2004) found IBES analysts’ earnings forecast dispersion to be significantly higher for the CARs of value stock (high book value to market value ratio) based portfolios than growth stock (low book value to market value ratio) based portfolios in the US market from 1983 through 2001.
However, some studies presented ambivalent results. Peterson and Peterson (1982), for example, used IBES analysts’ earnings forecast dispersion and stock returns from CRSP from December 1978 through November 1980 to indicate a positive relation between analysts’ earnings forecast dispersion and firm specific risk. However, further partitioning of the data revealed a significant positive relation between analysts’ earnings forecast dispersion and firm specific risk in the first time period from December 1978 through November 1979 and a significant negative correlation between analysts’ earnings forecast dispersion and firm specific risk in the second time period from December 1979 through November 1980. This set of mixed results was corroborated by Barry and Jennings (1992),
who demonstrated the lack of relation between estimation risk32 (proxied by analysts’
diversity of opinions using the dispersion of their earnings) and stock returns. Estimation risk was expected to increase returns but results have shown otherwise, suggesting dispersion may be a poor proxy for estimation risk.
Analysts’ earnings forecast dispersion has been shown to have a positive impact on future stock return volatility. Athanassakos and Kalimipalli (2003), using the IBES consensus forecast dispersion measure, showed a positive relation between analysts’ earnings forecast dispersion and future stock return volatility. Lobo and Tung (2000) drew a similar conclusion with IBES analysts’ forecast dispersion data displaying a positive relation with stock price dispersion.
Temporal and cross-sectional trends in earnings dispersion movements were evidenced in Ciccone and Etebari (2004) and Kwon (2002) respectively. Using IBES analysts’ earnings dispersion data from 1987 through 1998 in the US and seven Pacific-rim countries, namely Australia, New Zealand, Taiwan, Hong Kong, Japan, South Korea, and Thailand, Ciccone and Etebari (2004) showed the trend of dispersion reducing over time for the US, Australia and New Zealand. Asian countries such as Japan and Korea, rather, exhibited an opposing trend of increasing dispersion over the sample period. This display of regional differences in results suggests that Asian firms may not adhere to the earnings guidance style management policy carried out by US, Australian and New Zealand firms. On the other hand, a cross- sectional study of the properties of analysts’ earnings forecasts by Kwon (2002) revealed lower dispersion for high tech firms vis-à-vis low tech firms for the period 1990 through 1997.