HCBE Faculty Articles

ORCID

Rebecca Abraham 0000-0002-3144-7759

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Document Type

Article

Publication Title

Open Journal of Accounting

ISSN

2169-3404

Publication Date

7-2016

Abstract/Excerpt

This study identifies the predictors of positive earnings surprises at varying levels of earnings surprises under strong and weak business conditions (2014 and 2010, respectively). It measures the impact on surprises of a unique and diverse set of predictors such as analyst coverage and industry type which are security characteristics and sales and cash flow that emanate from financial statements. The study employs technology stocks that were found on the NASDAQ as such stocks have reported high positive earnings surprises from 2013-2015 [1]. The entire population of positive earnings surprises for 8316 NASDAQ stocks in 2010 and 2014 was used. Event studies were used to measure abnormal return and abnormal volume at earnings announcement, while multiple regressions tested the influence of the predictors of positive earnings surprises including number of analysts, sales, cash flow and industry type. Number of analysts significantly predicted positive earnings surprises of <20%, 21% - 30%, 31% - 100% and > 100% regardless of business condition, while sales and industry type showed similar results for weak business conditions. Cash flow explained positive earnings surprises in the 21% - 30% earnings surprises range for weak business conditions, while industry type was significant in the <20% and >100% earnings surprises categories for strong business conditions.

DOI

https://doi.org/10.4236/ojacct.2016.53004

Volume

5

Issue

3

First Page

25

Last Page

34

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 International License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.

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