The explanatory power of representative agent earnings momentum models

William Forbes, Aloysius Igboekwu

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)

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.
Original languageEnglish
Pages (from-to)473-492
JournalReview of Quantitative Finance and Accounting
Volume44
Issue number3
Early online date08 Nov 2013
DOIs
Publication statusPublished - Apr 2015

Keywords

  • Earnings momentum
  • Law of small numbers
  • Bayesian inference
  • G14
  • M4
  • G11

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