Abstract
We study the ranking of classified multi-attribute qualitative options. To obtain a full ranking of options within classes, qualitative options are mapped into quantitative ones. Current approaches, such as the Qualitative-Quantitative (QQ) method, use linear functions for ranking, hence performing well for linear and monotone options; however QQ underperforms in cases of non-linear and nonmonotone options. To address this problem, we propose a new QQ-based method in which we introduce copulas as an aggregation utility instead of linear functions. In addition, we analyze the behavior of different hierarchical structures of bivariate copulas to model the non-linear dependences among attributes and classes.
Keywords
- Archimedean Copula
- Linear Regression Function
- Clayton Copula
- Copula Family
- Inverse Cumulative Distribution Function
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Berg, D., Aas, K.: Models for construction of multivariate dependance: A comparison study. European Journal of Finance 15(7-8), 639–659 (2009)
Bohanec, M.: Odloˇcanje in modeli. DMFA, Ljubljana (2006) 3. Bohanec, M.: DEXi: Program for Multi-Attribute Decision Making: User’s manual : version
3.03. IJS Report DP-10707, Joˇzef Stefan Institute, Ljubljana (2011)
Bohanec, M., Rajkoviˇc, V.: DEX: An expert system shell for decision support. Sistemica 1, 145–157 (1990)
Bohanec, M., Urh, B., Rajkoviˇc, V.: Evaluation of options by combined qualitative and quantitative methods. Acta Psychologica 80, 67–89 (1992)
Bouy´e, E., Salmon, M.: Dynamic copula quantile regressions and tail area dynamic dependence in forex markets. European Journal Of Finance 15, 721–750 (2009)
Brown, L., Cai, T., Zhang, R., Zhao, L., Zhou, H.: A root-unroot transform and wavelet block thresholding approach to adaptive density estimation. unpublished (2005)
Fischer, M., Kock, C., Schluter, S., Weigert, F.: An empirical analysis of multivariate copula models. Quantitative Finance 9(7), 839–854 (2009)
Joe, H.: Multivariate Models and Dependence Consepts. Chapman and Hall (1997)
Kolev, N., Paiva, D.: Copula based regression models: A survey. Journal of Statistical Planning and Inference 139(11), 3847 – 3856 (2009)
Nelsen, R.B.: An Introduction to Copulas, 2nd edn. Springer, New York (2006)
Savu, C., Trade, M.: Hierarchical archimedean copulas. In: International Conference on High Frequency Finance. Konstanz, Germany (2006)
Trivedi, P., David, Z.: Copula Modeling: An Introduction for Practitioners. World Scientific Publishing (2006)
Wasserman, L.: All of Nonparametric Statistics. Springer Texts in Statistics, USA (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mileva-Boshkoska, B., Bohanec, M. (2012). Ranking of qualitative decision options using copulas. In: Klatte, D., Lüthi, HJ., Schmedders, K. (eds) Operations Research Proceedings 2011. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29210-1_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-29210-1_17
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29209-5
Online ISBN: 978-3-642-29210-1
eBook Packages: Business and EconomicsBusiness and Management (R0)