Extrapolation Bias in Explaining the Asset Growth Anomaly: Evidence from Analysts’ Multi-Period Earnings Forecasts

41 Pages Posted: 16 Jan 2014 Last revised: 16 Oct 2015

See all articles by Hyungjin Cho

Hyungjin Cho

Inha University - College of Business Administration

Sunhwa Choi

Seoul National University - Business School

Lee-Seok Hwang

Seoul National University - College of Business Administration

Woo-Jong Lee

Seoul National University

Date Written: October 2015

Abstract

Using analysts’ multi-period earnings forecasts, this paper investigates whether analyst forecast errors are related to asset growth and, if so, to what extent analysts’ optimism for high-growth firms can explain the asset growth anomaly. We find that analyst forecasts are more optimistic for firms with high asset growth, particularly for longer-term forecasts (e.g., two- and three-year-ahead forecasts than one-year-ahead forecasts). We also find that analysts’ optimism for high-growth firms is more pronounced for (1) firms that have maintained similar levels of growth in recent periods, (2) firms with higher information uncertainty, and (3) forecasts with longer forecast horizons (e.g., forecasts issued far before fiscal year end). Adding forecast errors to a growth-return regression substantially reduces the coefficient on asset growth, suggesting an important role of forecast errors in the growth anomaly. Path analysis suggests that analysts’ long-term forecast errors, but not short-term forecast errors, are important mediators through which biased expectations about asset growth are incorporated into stock returns. Overall, our findings support the extrapolation bias explanation for the asset growth anomaly.

Keywords: analyst forecast, growth anomaly, investment anomaly, extrapolation bias

Suggested Citation

Cho, Hyungjin and Choi, Sunhwa and Hwang, Lee-Seok and Lee, Woo-Jong, Extrapolation Bias in Explaining the Asset Growth Anomaly: Evidence from Analysts’ Multi-Period Earnings Forecasts (October 2015). Available at SSRN: https://ssrn.com/abstract=2378215 or http://dx.doi.org/10.2139/ssrn.2378215

Hyungjin Cho

Inha University - College of Business Administration ( email )

Incheon
Korea, Republic of (South Korea)

Sunhwa Choi (Contact Author)

Seoul National University - Business School ( email )

Seoul
Korea, Republic of (South Korea)

Lee-Seok Hwang

Seoul National University - College of Business Administration ( email )

Seoul, 151-742
Korea, Republic of (South Korea)

Woo-Jong Lee

Seoul National University ( email )

Gwanak-ro 1, Gwanak-gu
Seoul, 08826
Korea, Republic of (South Korea)

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