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Abstract
ABSTRACT Purpose: This research examines the superiority of analysts over random walk models in forecasting the results of publicly-traded Brazilian companies in the short and long term. Originality/value: The literature indicates the uncontested superiority of market analysts because of their temporal and informational advantages. However, recent international studies call for a re-evaluation of this superiority, indicating that, for certain company characteristics, and primarily for long-term estimates, the superiority of analysts is not confirmed. Design/methodology/approach: This work evaluates the profit forecasting of analysts and simple and growth random walk models over the short and long term over 2010-2015 for publicly traded Brazilian companies, using the information available for the period with annual intervals. Findings: The results indicate: 1. the greater forecasting accuracy of simple random walk models compared to the growth random walk models; and 2. the greater forecasting accuracy of random walk models overall, with analyst forecasts only being superior for cases with three months of lag. The evidence suggests the forecasting superiority of the random walk models when compared to the market analysts' forecasts. The results suggest low efficiency of the forecasts of market analysts for the forecast of future results of publicly traded Brazilian companies in the analyzed period.
Highlights
Company earnings constitute important information for investment decision making. Ramnath, Rock, and Shane (2008) indicate that market analysts are important agents in the task of evaluating investments
The accuracy of the estimates from these models is inferior to those obtained from simple random walk models
The study marks a departure from the traditional literature, which argues that market analysts are superior in forecasting future company results and have informational and temporal advantages over time-series models (Brown, Hagerman et al, 1987, Brown et al, 1987; Fried & Givoly, 1982; Hopwood & McKeown, 1982; O’Brien, 1988)
Summary
Company earnings constitute important information for investment decision making. Ramnath, Rock, and Shane (2008) indicate that market analysts are important agents in the task of evaluating investments. As analysts are offered various incentives, they generally present estimates with a positive bias (Bradshaw, Drake, Myers, & Myers, 2012; Dugar & Nathan, 1995; Francis & Philbrick, 1993; Gatsios, Lima, & Assaf Neto, 2016; Gu & Wu, 2003; Martinez, 2007; McNichols & O’Brien, 1997). Another option for predicting company earnings is the use of time-series forecasting models (Goojier & Hyndman, 2006). In this line of research, studies arguing for the superiority of market analysts over time-series models compare the accuracy of their earnings forecasts
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