Abstract

http://ssrn.com/abstract=2376039
 


 



A Study of Analyst Forecast Reliability in Australia


Alina Maydybura


University of Wollongong - School of Accounting and Finance

Dionigi Gerace


University of Sydney

Brian Andrew


University of Wollongong - School of Accounting and Finance

2013

Journal of Applied Research in Accounting and Finance (JARAF), Vol. 8, No. 2, 2013

Abstract:     
The purpose of this paper is to determine whether time weighted consensus estimates offer a more effective method for predicting company actual EPS figures than simple mean or median analysis. The study aims to construct a more comprehensive earnings forecast signal using analyst earnings forecasts that have been weighted based on the timeliness of updates. Aimed at extracting valuable information from timely analyst forecasts, the time weighted earnings signal (TWES) methodology allows extracting valuable information from analysts who possess some unique insights about the market and issue their updates more frequently. One would expect the time signal to reflect a more realistic representation of analyst estimate changes and thus be more effective in predicting the companies’ reported EPS than the mean and median.

Number of Pages in PDF File: 25

Keywords: Accounting, Finance

JEL Classification: M40, M41

Accepted Paper Series


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Date posted: January 9, 2014  

Suggested Citation

Maydybura, Alina and Gerace, Dionigi and Andrew, Brian, A Study of Analyst Forecast Reliability in Australia (2013). Journal of Applied Research in Accounting and Finance (JARAF), Vol. 8, No. 2, 2013. Available at SSRN: http://ssrn.com/abstract=2376039

Contact Information

Alina Maydybura
University of Wollongong - School of Accounting and Finance ( email )
Northfields Avenue
Wollongong, NSW 2522
Australia
Dionigi Gerace (Contact Author)
University of Sydney ( email )
University of Sydney
Sydney, NSW 2006
Australia
Brian Andrew
University of Wollongong - School of Accounting and Finance ( email )
Northfields Avenue
Wollongong, NSW 2522
Australia
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