Analysis Earnings Forecast: An Alternative Data Source for Failure Prediction.

Abstract

This study investigates four properties of earnings forecasts made by financial analysts to determine if systematic differences in these properties exists failing and healthy firms. The four properties are: The level of forecasts, forecast error, forecast bias, and forecast dispersion. Measures reflecting the four properties are used in models to distinguish failing and healthy firms and predict future bankruptcy. Results indicate that measures developed from analysts forecasts of future earnings can be exploited to distinguish failing from healthy firms.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1986
Accession Number
ADA186550

Entities

People

  • O. D. Moses

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accounting
  • Accuracy
  • Artificial Intelligence
  • Bankruptcy
  • Bias
  • Classification
  • Contracts
  • Data Science
  • Dispersions
  • Errors
  • Information Science
  • Military Research
  • Notation
  • Security
  • Three Dimensional
  • Verification
  • Verification Tests

Readers

  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation
  • Economics