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The golden rule of forecasting: objections, refinements, and enhancements

Title	The golden rule of forecasting: objections, refinements, and enhancements
Author	Soyer, Emre, Hogarth, R. M.
Publication Date:	2015-08
Publication Place	- Elsevier
Subject	Conservative, Golden Rule, Scenario, Simulation
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	0148-2963
Record ID	6e9f70ce-a482-437c-8edb-8946a2d7db36
Library Location	Business Administration
Date	2015-08
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	In providing a “golden rule” for forecasting, Armstrong, Green, and Graefe (this issue) raise aspirations that reliable forecasting is possible. They advocate a conservative approach that mainly involves extrapolating from the present. We comment on three issues that relate to their proposed Golden Rule: its scope of application, the importance of highly improbable events, and the challenges of communicating forecasts.
DOI	10.1016/j.jbusres.2015.03.029
Cilt	68

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Özyeğin University

The golden rule of forecasting: objections, refinements, and enhancements

Author Soyer, Emre, Hogarth, R. M.

Publication Date 2015-08

Publication Place - Elsevier

Subject Conservative, Golden Rule, Scenario, Simulation

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 0148-2963

Record ID 6e9f70ce-a482-437c-8edb-8946a2d7db36

Library Location Business Administration

Date 2015-08

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text In providing a “golden rule” for forecasting, Armstrong, Green, and Graefe (this issue) raise aspirations that reliable forecasting is possible. They advocate a conservative approach that mainly involves extrapolating from the present. We comment on three issues that relate to their proposed Golden Rule: its scope of application, the importance of highly improbable events, and the challenges of communicating forecasts.

DOI 10.1016/j.jbusres.2015.03.029

Cilt 68