JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A New Approach to Risk Comparison via Uncertain Measure
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A New Approach to Risk Comparison via Uncertain Measure
Li, Shengguo; Peng, Jin;
  PDF(new window)
 Abstract
This paper presents a new approach to risk comparison in uncertain environment. Based on the uncertainty theory, some uncertain risk measures and risk comparison rules are proposed. Afterward the bridges are built between uncertain risk measures and risk comparison rules. Finally, several comparable examples are given.
 Keywords
Uncertainty Theory;Uncertain Measure;Uncertainty Distribution;Risk Analysis;
 Language
English
 Cited by
1.
Two Uncertain Programming Models for Inverse Minimum Spanning Tree Problem,;;;

Industrial Engineering and Management Systems, 2013. vol.12. 1, pp.9-15 crossref(new window)
1.
Two Uncertain Programming Models for Inverse Minimum Spanning Tree Problem, Industrial Engineering and Management Systems, 2013, 12, 1, 9  crossref(new windwow)
2.
Efficient VaR and CVaR Measurement via Stochastic Kriging, INFORMS Journal on Computing, 2016, 28, 4, 629  crossref(new windwow)
3.
Uncertain expected utility function and its risk premium, Journal of Intelligent Manufacturing, 2017, 28, 3, 581  crossref(new windwow)
 References
1.
Artzner, P., Delbaen, F., Eber, J., and Heath, D. (1997), Thinking coherently, Risk, 10, 68-71.

2.
Barrett, G. F. and Donald, S. G. (2003), Consistent tests for stochastic dominance, Econometrica, 71, 71-104. crossref(new window)

3.
Guldimann, T. M. (1995), Risk Metrics TM: Technical Document, JPMorgan, New York, NY.

4.
Lee, E. S. and Li, R.-J. (1988), Comparison of fuzzy numbers based on the probability measure of fuzzy events, Computers and Mathematics with Applications, 15, 887-896. crossref(new window)

5.
Lee, L.-W. and Chen, S.-M. (2008), Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations, Expert Systems with Applications, 34, 2763-2771. crossref(new window)

6.
Liu, B. (2007), Uncertainty Theory (2nd ed.), Springer, Berlin, Germany.

7.
Liu, B. (2009), Some research problems in uncertainty theory, Journal of Uncertain Systems, 3, 3-10.

8.
Liu, B. (2010a), Uncertainty Theory: A Branch of Mathematics for Modeling Human Uncertainty, Springer, Berlin, Germany.

9.
Liu, B. (2010b), Uncertain risk analysis and uncertain reliability analysis, Journal of Uncertain Systems, 4, 163-170.

10.
Markowitz, H. (1952), Portfolio selection, The Journal of Finance, 7, 77-91.

11.
Nojavan, M. and Ghazanfari, M. (2006), A fuzzy ranking method by desirability index, Journal of Intelligent and Fuzzy Systems, 17, 27-34.

12.
Peng, J. (2008), Measuring fuzzy risk by credibilistic value at risk, Proceedings of the 3rd International Conference on Innovative Computing Information and Control, Dalian, China, 270.

13.
Peng, J. (2009a), Value at risk and tail value at risk in uncertain environment, Proceedings of the 8th International Conference on Information and Management Sciences, Kunming, China, 787-793.

14.
Peng, J. (2009b), Average value at risk in fuzzy risk analysis, Advances in Intelligent and Soft Computing, 62, 1303-1313. crossref(new window)

15.
Peng, J. and Li, S. (2010), Spectral measure of uncertain risk, Proceedings of the 1st International Conference on Uncertain Theory, Urumchi and Kashi, China, 1-7.

16.
Peng, J. and Li, S. (2011), Distortion risk measures of uncertain systems, Proceedings of the 9th International Conference on Reliability, Maintainability and Safety, Guiyang, China, 460-467.

17.
Peng, J., Jiang, Q., and Rao, C. (2007), Fuzzy dominance: a new approach for ranking fuzzy variables via credibility measure, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15, 29-41. crossref(new window)

18.
Peng, J., Mok, H. M. K., and Tse, W.-M. (2005), Fuzzy dominance based on credibility distributions, Proceedings of the 2nd International Conference on Fuzzy Systems and Knowledge Discovery, Changsha, China, 295-303.

19.
Shaked, M. and Shanthikumar, J. G. (1994), Stochastic Orders and Their Applications, Academic Press, Boston, MA.

20.
Tran, L. and Duckstein, L. (2002), Comparison of fuzzy numbers using a fuzzy distance measure, Fuzzy Sets and Systems, 130, 331-341. crossref(new window)

21.
Zadeh, L. A. (1965), Fuzzy sets, Information and Control, 8, 338-353. crossref(new window)

22.
Zmeskal, Z. (2005), Value at risk methodology of international index portfolio under soft conditions (fuzzy- stochastic approach), International Review of Financial Analysis, 14, 263-275. crossref(new window)