The explanatory power of representative agent earnings momentum models

William Forbes () and Aloysius Igboekwu ()

Review of Quantitative Finance and Accounting, 2015, vol. 44, issue 3, 473-492

Abstract: This paper examines the predictive performance of two representative agent models of earnings momentum using the US S & P 500 sample frame in the years 1991–2006. For successive sequences of quarterly earnings outcomes over a three year horizon of quarterly increases/decreases, etc., we ask whether these models can capture the likelihood of reversion and, secondly, the stock market response to observed quarterly earnings change sequences for our chosen sample. We find evidence of a far greater frequency of persistent quarterly earnings rises and hence a more muted reaction to their occurrence. Persistent losses are both far less common and more salient in their impact on stock prices. Copyright Springer Science+Business Media New York 2015

Keywords: Earnings momentum; Law of small numbers; Bayesian inference; G14; M4; G11 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11156-013-0414-4

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