Author(s)

Rebecca Abraham, Charles Harrington

Huizenga College of Business, Nova Southeastern University, Fort Lauderdale, FL, USA.

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.

Positive Earnings Surprise, Analyst Coverage, Cash Flow, Industry Type

Abraham, R. and Harrington, C. (2016) Predictors of the Degree of Positive Earnings Surprises. Open Journal of Accounting, 5, 25-34. doi: 10.4236/ojacct.2016.53004.