TY - JOUR
T1 - Stochastic dominance and risk measure
T2 - A decision-theoretic foundation for VaR and C-VaR
AU - Ma, Chenghu
AU - Wong, Wing-Keung
N1 - Funding Information:
The authors thank the Editor, Professor Lorenzo Peccati, for his helpful comments which help to improve our manuscript significantly. We also show our appreciation to Professor Jan Dhaene and Professor Hans Föllmer for their valuable comments. The first author acknowledge support from Nature Science Foundation of China ( #70871100 ). The second author acknowledge support from Research Grants Council of Hong Kong ( #202809 ).
PY - 2010/12
Y1 - 2010/12
N2 - Is it possible to obtain an objective and quantifiable measure of risk backed up by choices made by some specific groups of rational investors? To answer this question, in this paper we establish some behavior foundations for various types of VaR models, including VaR and conditional-VaR, as measures of downside risk. In this paper, we will establish some logical connections among VaRs, conditional-VaR, stochastic dominance, and utility maximization. Though supported to some extents with unanimous choices by some specific groups of expected or non-expected-utility investors, VaRs as profiles of risk measures at various levels of risk tolerance are not quantifiable - they can only provide partial and incomplete risk assessments for risky prospects. We also include in our discussion the relevant VaRs and several alternative risk measures for investors; these alternatives use somewhat weaker assumptions about risk-averse behavior by incorporating a mean-preserving-spread. For this latter group of investors, we provide arguments for and against the standard deviation versus VaR and conditional-VaRs as objective and quantifiable measures of risk in the context of portfolio choice.
AB - Is it possible to obtain an objective and quantifiable measure of risk backed up by choices made by some specific groups of rational investors? To answer this question, in this paper we establish some behavior foundations for various types of VaR models, including VaR and conditional-VaR, as measures of downside risk. In this paper, we will establish some logical connections among VaRs, conditional-VaR, stochastic dominance, and utility maximization. Though supported to some extents with unanimous choices by some specific groups of expected or non-expected-utility investors, VaRs as profiles of risk measures at various levels of risk tolerance are not quantifiable - they can only provide partial and incomplete risk assessments for risky prospects. We also include in our discussion the relevant VaRs and several alternative risk measures for investors; these alternatives use somewhat weaker assumptions about risk-averse behavior by incorporating a mean-preserving-spread. For this latter group of investors, we provide arguments for and against the standard deviation versus VaR and conditional-VaRs as objective and quantifiable measures of risk in the context of portfolio choice.
KW - Decision analysis
KW - Risk analysis
KW - Risk attributes
KW - Utility
KW - Stochastic dominance
UR - http://www.scopus.com/inward/record.url?scp=77955554523&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2010.05.043
DO - 10.1016/j.ejor.2010.05.043
M3 - Journal article
AN - SCOPUS:77955554523
SN - 0377-2217
VL - 207
SP - 927
EP - 935
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -