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Predicting long-term earnings growth from multiple information sources

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Predicting long-term earnings growth from multiple information sources. / Gao, Zhan; Wu, Wan-Ting.

In: International Review of Financial Analysis, Vol. 32, 03.2014, p. 71-84.

Research output: Contribution to journalJournal articlepeer-review

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Gao, Z & Wu, W-T 2014, 'Predicting long-term earnings growth from multiple information sources', International Review of Financial Analysis, vol. 32, pp. 71-84. https://doi.org/10.1016/j.irfa.2014.01.009

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Gao, Zhan ; Wu, Wan-Ting. / Predicting long-term earnings growth from multiple information sources. In: International Review of Financial Analysis. 2014 ; Vol. 32. pp. 71-84.

Bibtex

@article{4f1c3b8747634cb6bfe42efd91a08f60,
title = "Predicting long-term earnings growth from multiple information sources",
abstract = "While expected long-term earnings growth plays a pivotal role in valuation and investment applications, its common proxy, analysts{\textquoteright} long-term growth forecasts (LTG), is well known for being over-optimistic. Guided by a stylized growth model, this paper uses three information sources to improve growth prediction—analysts{\textquoteright} forecasts, stock prices, and financial statements. We find that the growth model using LTG, past earnings growth, the forward earnings-to-price ratio and past returns as predictors is unbiased and most accurate among the models considered in this paper. We further show that this growth prediction results in higher trading profits, more accurate equity predictions, and more reliable estimates of cost of equity. The findings suggest that this improvement in growth prediction leads to economically significant consequences in valuation and investment applications.",
keywords = "Long-term growth, earnings growth prediction , analysts{\textquoteright} forecasts, Equity valuation, Valuation ratio",
author = "Zhan Gao and Wan-Ting Wu",
year = "2014",
month = mar,
doi = "10.1016/j.irfa.2014.01.009",
language = "English",
volume = "32",
pages = "71--84",
journal = "International Review of Financial Analysis",
issn = "1057-5219",
publisher = "Elsevier Inc.",

}

RIS

TY - JOUR

T1 - Predicting long-term earnings growth from multiple information sources

AU - Gao, Zhan

AU - Wu, Wan-Ting

PY - 2014/3

Y1 - 2014/3

N2 - While expected long-term earnings growth plays a pivotal role in valuation and investment applications, its common proxy, analysts’ long-term growth forecasts (LTG), is well known for being over-optimistic. Guided by a stylized growth model, this paper uses three information sources to improve growth prediction—analysts’ forecasts, stock prices, and financial statements. We find that the growth model using LTG, past earnings growth, the forward earnings-to-price ratio and past returns as predictors is unbiased and most accurate among the models considered in this paper. We further show that this growth prediction results in higher trading profits, more accurate equity predictions, and more reliable estimates of cost of equity. The findings suggest that this improvement in growth prediction leads to economically significant consequences in valuation and investment applications.

AB - While expected long-term earnings growth plays a pivotal role in valuation and investment applications, its common proxy, analysts’ long-term growth forecasts (LTG), is well known for being over-optimistic. Guided by a stylized growth model, this paper uses three information sources to improve growth prediction—analysts’ forecasts, stock prices, and financial statements. We find that the growth model using LTG, past earnings growth, the forward earnings-to-price ratio and past returns as predictors is unbiased and most accurate among the models considered in this paper. We further show that this growth prediction results in higher trading profits, more accurate equity predictions, and more reliable estimates of cost of equity. The findings suggest that this improvement in growth prediction leads to economically significant consequences in valuation and investment applications.

KW - Long-term growth

KW - earnings growth prediction

KW - analysts’ forecasts

KW - Equity valuation

KW - Valuation ratio

U2 - 10.1016/j.irfa.2014.01.009

DO - 10.1016/j.irfa.2014.01.009

M3 - Journal article

VL - 32

SP - 71

EP - 84

JO - International Review of Financial Analysis

JF - International Review of Financial Analysis

SN - 1057-5219

ER -