Credibilistic Risk Aversion

Quantitative Finance, Volume 17, Issue 7, pp. 1135-1145, 2017, DOI: 10.1080/14697688.2016.1264617

20 Pages Posted: 18 Nov 2016 Last revised: 11 Jun 2017

See all articles by Yuanyuan Liu

Yuanyuan Liu

Shanghai University, School of Management

Jian Zhou

Shanghai University, School of Management

Athanasios A. Pantelous

Monash University - Department of Econometrics & Business Statistics

Date Written: November 18, 2016

Abstract

In the probabilistic risk aversion approach, risks are presumed as random variables with known probability distributions. However, in some practical cases, for example, due to the absence of historical data, the inherent uncertain characteristic of risks or different subject judgements from the decision makers may be hard or not appropriate to be estimated with probability distributions. Therefore the traditional probabilistic risk aversion theory is ineffective. Thus, in order to deal with these cases, we suggest to measure those kinds of risks as fuzzy variables, and accordingly to present an alternative risk aversion approach by employing the credibility theory. In the present paper, first, the definition of credibilistic risk premium proposed by Georgescu and Kinnunen (2013) is revised by taking the initial wealth into consideration, and provide a general method to compute the credibilistic risk premium. Secondly, regarding the risks represented with the commonly used LR fuzzy intervals, a simple calculation formula for the local credibilistic risk premium is put forward. Finally, in a global sense, several equivalent propositions for the comparative risk aversion under the credibility measurement are provided. Illustrated examples are presented to show the applicability of the theoretical findings.

Keywords: Risk Aversion, LR Fuzzy Interval, Credibility Theory, Credibilistic Risk Premium

JEL Classification: G1, D81, G12

Suggested Citation

Liu, Yuanyuan and Zhou, Jian and Pantelous, Athanasios A., Credibilistic Risk Aversion (November 18, 2016). Quantitative Finance, Volume 17, Issue 7, pp. 1135-1145, 2017, DOI: 10.1080/14697688.2016.1264617, Available at SSRN: https://ssrn.com/abstract=2872194

Yuanyuan Liu

Shanghai University, School of Management ( email )

149 Yanchang Road
SHANGDA ROAD 99
Shanghai 200072, SHANGHAI 200444
China

Jian Zhou (Contact Author)

Shanghai University, School of Management ( email )

149 Yanchang Road
SHANGDA ROAD 99
Shanghai 200072, SHANGHAI 200444
China

Athanasios A. Pantelous

Monash University - Department of Econometrics & Business Statistics ( email )

Wellington Road
Clayton, Victoria 3168
Australia

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