Earnings smoothness and individual forecasts: some experimental evidence Wei Zhu 12/7/2018.

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Presentation transcript:

Earnings smoothness and individual forecasts: some experimental evidence Wei Zhu 12/7/2018

Research question In this study, I investigate to what extent earnings smoothness (a parameter in a hypothetic earnings process) influences individuals’ earnings forecast properties Graham et al. (2005): smooth earnings ease the analyst’s task of predicting future earnings. Predictability of earnings is an over-arching concern among CFOs McInnis (2009) examines the Value Line analysts’ forecasts. He finds that Value Line forecasts tend to be much more optimistic for firms with more volatile earnings Barberis et al. (1998) suggests that for firms with a long string of positive earnings surprises, investors tend to be more optimistic The relationship between earnings smoothness and individual forecasts remains a puzzle. 12/7/2018

Experiment design 12/7/2018

Research hypothesis H1a: holding growth scenario constant (be constant), smoother earnings series (lower δ) leads to lower absolute value of forecast errors. H1b: when main trend of earnings is growing, smoother earnings series (lower δ) is associated with more optimistic forecast errors; when the main trend of earnings is declining, smoother earnings series is associated with more pessimistic forecast errors. H2: holding growth scenario constant (be constant), smoother earnings series (lower δ) is associated with smaller forecast dispersion among subjects. H3: absolute value of one-year out earnings forecast error is smaller than that of two-year out forecast error. H4: individual’s absolute values of forecast error for different hypothetical firms are positively correlated. 12/7/2018

Variable definition Earnings forecast benchmark 12/7/2018

Subjects’ forecasting strategy 12/7/2018

Test of H1 12/7/2018

Test of H1 12/7/2018

Test of H2 12/7/2018

Test of H2 12/7/2018

Test of H3 12/7/2018

Test of H3 12/7/2018

Test of H4 12/7/2018

Test of H4 12/7/2018

Conclusions Smoother earnings is associated with more accurate forecasts in terms of lower absolute value of forecast errors (either standardized or un-standardized), holding growth scenario constant. There is no clear evidence that smoother earnings is associated with either more optimistic or more pessimistic forecasts. There is only weak evidence that smoother earnings is associated with lower forecast dispersion. One-year out forecasts do not appear to have lower absolute value of forecast errors than two-year out forecasts. Subjects do not exhibit consistent abilities to make more accurate earnings forecast. Subjects only rely on the most recent earnings to make forecasts while ignoring the information contained in the longer history. 12/7/2018