Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Business Valuation and Economic Loss Analysis

Editor-in-Chief: Ewing, Bradley T. / Hoffman, Jim

1 Issue per year


CiteScore 2017: 0.32

SCImago Journal Rank (SJR) 2017: 0.160
Source Normalized Impact per Paper (SNIP) 2017: 0.622

Online
ISSN
1932-9156
See all formats and pricing
More options …

ARIMA Forecasting: Variables without a Cause

Michael Sack Elmaleh
Published Online: 2016-10-13 | DOI: https://doi.org/10.1515/jbvela-2016-0009

Abstract

ARIMA forecast methods offer short term accuracy but have severe limitations in the appraisal context. ARIMA forecasts fail to identify or model causal variables, require more data points than are usually available and are very difficult to explain to non-statisticians. Better forecast alternatives are available to appraisers.

Keywords: explanatory clarity; ARIMA forecasts; causal variables

About the article

Published Online: 2016-10-13

Published in Print: 2017-05-24


Citation Information: Journal of Business Valuation and Economic Loss Analysis, Volume 12, Issue 1, Pages 141–143, ISSN (Online) 1932-9156, ISSN (Print) 2194-5861, DOI: https://doi.org/10.1515/jbvela-2016-0009.

Export Citation

© 2017 Walter de Gruyter GmbH, Berlin/Boston.Get Permission

Comments (0)

Please log in or register to comment.
Log in