A fuzzy risk attitude classification based on prospect theory

Li, Yang; Portmann, Edy (November 2012). A fuzzy risk attitude classification based on prospect theory. In: Proceedings of the 2012 International Conference on Fuzzy Theory and Its Applications (pp. 137-143). Taichung, Taiwan: IEEE / Institute of Electrical and Electronics Engineers Incorporated 10.1109/iFUZZY.2012.6409689

[img] Text
1042-1.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (663kB) | Request a copy

Traditional methods do not actually measure peoples’ risk attitude naturally and precisely. Therefore, a fuzzy risk attitude classification method is developed. Since the prospect theory is usually considered as an effective model of decision making, the personalized parameters in prospect theory are firstly fuzzified to distinguish people with different risk attitudes, and then a fuzzy classification database schema is applied to calculate the exact value of risk value attitude and risk be- havior attitude. Finally, by applying a two-hierarchical clas- sification model, the precise value of synthetical risk attitude can be acquired.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Portmann, Edy

Subjects:

600 Technology > 650 Management & public relations

ISBN:

978-1-4673-2057-3

Publisher:

IEEE / Institute of Electrical and Electronics Engineers Incorporated

Language:

English

Submitter:

Sara D'Onofrio

Date Deposited:

03 Apr 2014 16:06

Last Modified:

26 Jun 2016 01:49

Publisher DOI:

10.1109/iFUZZY.2012.6409689

Uncontrolled Keywords:

fuzzy classification, Parameters, Prospect Theory Application, Risk Attitude

BORIS DOI:

10.7892/boris.45572

URI:

https://boris.unibe.ch/id/eprint/45572

Actions (login required)

Edit item Edit item
Provide Feedback