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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

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ARIMA Forecasting: Variables without a Cause

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


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

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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.

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