Two Stage Fuzzy Methodology to Evaluate the Credit Risks of Investment Projects
The work proposes a decision support methodology
for the credit risk minimization in selection of investment projects.
The methodology provides two stages of projects’ evaluation.
Preliminary selection of projects with minor credit risks is made
using the Expertons Method. The second stage makes ranking of
chosen projects using the Possibilistic Discrimination Analysis
Method. The latter is a new modification of a well-known Method of
Fuzzy Discrimination Analysis.
[1] R. E. Bellman and L. A. Zadeh, "Decision-Making in a Fuzzy
Environment”, Management Science, 17(4), 1970, B-141-B-164.
[2] D. Dubois and H. Prade, Possibility Theory: An Approach to
Computerized Processing of Uncertainty. New-York: Plenum Press,
1988.
[3] A. Kaufmann, "Theory of expertons and fuzzy logic”, Fuzzy Sets and
Systems, 28(3), 1988, 295-304.
[4] A. Kaufmann, Expert Appraisements and Counter-Appraisements with
Experton Processes, Analysis and Management of Uncertainty: Theory
and Applications, North Holland, Amsterdam, 1992.
[5] G. J. Klir and M. J. Wierman, Uncertainty-Based Information. Elements
of Generalized Information Theory. Second edition. Studies in Fuzziness
and Soft Computing, Physica-Verlag, Heidelberg, 1999.
[6] I. Khutsishvili, "The Combined Decision Making Technology based on
the Statistical and Fuzzy Analysis and its Application in Forecast’s
Modeling”, WSEAS Transactions on Systems, 8(7), 2009, 891-901.
[7] I. Khutsishvili and G. Sirbiladze, "Decision Support’s Precising
Technology in the Investment Project Risk Management”, In:
Proceedings of the 11th WSEAS International Conference on Automatic
Control, Modelling and Simulation (ACMOS ‘09), Istanbul, Turkey,
2009, 303-311.
[8] B. Liu, "Toward fuzzy optimization without mathematical ambiquity”,
Fuzzy Optimization and Decision Making, 1(1), 2002, 43-63.
[9] D. Norris, B. W. Pilsworth and J. F. Baldwin, "Medical Diagnosis from
patient records – A method using fuzzy discrimination and connectivity
analysis”, Fuzzy Sets and Systems, 23, 1987, 73-87.
[10] D. Ruan, J. Kacprzyk and M. Fedrizzi, Soft Computing for Risk
Evaluation and Management: Applications in Technology, Environmenf
and Finance. Studies in Fuzziness and Soft Computing. Heidelberg, New
York: Physica-Verlag, 2001.
[11] G. Sirbiladze, A. Sikharulidze and G. Korakhashvili, "Decision-making
Aiding Fuzzy Informational Systems in Investments. Part I –
Discrimination Analysis in Investment Projects”, Proceedings of Iv.
Javakhishvili Tbilisi State University. Applied Mathematics and
Computer Sciences, 353 (22-23), 2003, 77-94.
[12] G. Sirbiladze and T. Gachechiladze, "Restored fuzzy measures in expert
decision-making ”, Information Sciences, 169 (1/2), 2005, 71-95.
[13] G. Sirbiladze and A. Sikharulidze, "Weighted Fuzzy Averages in Fuzzy
Environment, Parts I, II”, International Journal of Uncertainty,
Fuzziness and Knowledge-Based Systems, 11(2), 2003, 139-157, 159-
172.
[14] G. Sirbiladze, "Decision Precising Technologies in Decision Making
Systems”, Plenary Speech. In: N. Mastorakis, M. Demiralp, I. Rudas, C.
A. Bulucea, L. Rogozea (Eds.), Proc.of the Applied Computing
Conference 2009, ACC '09, Vouliagmeni, Athens, Greece, 2009, pp. 27-
28.
[15] G. Sirbiladze, A. Sikharulidze and N. Sirbiladze, "Generalized Weighted
Fuzzy Expected Values in Uncertainty Environment”, In: L. A. Zadeh, J.
Kacprzyk, N. Mastorakis, A. Kuri-Morales, P. Borne, L. Kazovsky
(Eds.), Proc. 9th WSEAS Int. Conf. on Artificial Intelligence, Knowledge
Engineering and Data Bases, AIKED '10, University of Cambridge, UK,
2010, pp. 59-65.
[16] G. Sirbiladze, "Fuzzy dynamic programming problem for extremal
fuzzy dynamic systems”, In: W. A. Lodwick and J. Kacprzyk (Eds.)
Fuzzy Optimization: Recent Developments and Applications, Studies in
Fuzziness and Soft Computing, 254, Heidelberg: Physica-Verlag, 231-
270, 2010.
[17] G. Sirbiladze, "Fuzzy Identification Problem for Continuous Extremal
Fuzzy Dynamic System”, Fuzzy Optimization and Decision Making, 9
(3), 2010, 233-274.
[18] G. Sirbiladze, I. Khutsisvili and P. Dvalishvili, "Decision Precising
Fuzzy Technology to Evaluate the Credit Risks of Investment Projects”,
IEEE 10-th International Conference on Intelligent Systems Desigh and
Applications (ISDA 2010), Cairo, Egypt, 2010, 103-108.
[19] G.Sirbiladze, I. Khutsishvili and B. Ghvaberidze, "Multistage decisionmaking
fuzzy methodology for optimal investments based on experts’
evaluations”, European Journal of Operational Research, 232(1), 2014,
169–177.
[20] D. Wu, Y. Zhang, D. Wu and D. L. Olson, "Fuzzy multi-objective
programming for supplier selection and risk modeling: A possibility
approach”, European Journal of Operational Research, 200(3), 2010,
774-787
[21] R. R. Yager, "On the Evalution of Uncertain Courses of Action”, Fuzzy
Optimization and Decision Making, 1(1), 2002, 13-41.
[22] R. R.Yager, "Aggregation of ordinal information”, Fuzzy Optimization
and Decision Making, 6(3), 2007, 199-219.
[23] L. Yu, S. Wang and K. K. Lai, "An intelligent-agent-based fuzzy group
decision making model for financial multicriteria decision support: The
case of credit scoring”, European Journal of Operational Research,
195(3), 2009, 942-959.
[1] R. E. Bellman and L. A. Zadeh, "Decision-Making in a Fuzzy
Environment”, Management Science, 17(4), 1970, B-141-B-164.
[2] D. Dubois and H. Prade, Possibility Theory: An Approach to
Computerized Processing of Uncertainty. New-York: Plenum Press,
1988.
[3] A. Kaufmann, "Theory of expertons and fuzzy logic”, Fuzzy Sets and
Systems, 28(3), 1988, 295-304.
[4] A. Kaufmann, Expert Appraisements and Counter-Appraisements with
Experton Processes, Analysis and Management of Uncertainty: Theory
and Applications, North Holland, Amsterdam, 1992.
[5] G. J. Klir and M. J. Wierman, Uncertainty-Based Information. Elements
of Generalized Information Theory. Second edition. Studies in Fuzziness
and Soft Computing, Physica-Verlag, Heidelberg, 1999.
[6] I. Khutsishvili, "The Combined Decision Making Technology based on
the Statistical and Fuzzy Analysis and its Application in Forecast’s
Modeling”, WSEAS Transactions on Systems, 8(7), 2009, 891-901.
[7] I. Khutsishvili and G. Sirbiladze, "Decision Support’s Precising
Technology in the Investment Project Risk Management”, In:
Proceedings of the 11th WSEAS International Conference on Automatic
Control, Modelling and Simulation (ACMOS ‘09), Istanbul, Turkey,
2009, 303-311.
[8] B. Liu, "Toward fuzzy optimization without mathematical ambiquity”,
Fuzzy Optimization and Decision Making, 1(1), 2002, 43-63.
[9] D. Norris, B. W. Pilsworth and J. F. Baldwin, "Medical Diagnosis from
patient records – A method using fuzzy discrimination and connectivity
analysis”, Fuzzy Sets and Systems, 23, 1987, 73-87.
[10] D. Ruan, J. Kacprzyk and M. Fedrizzi, Soft Computing for Risk
Evaluation and Management: Applications in Technology, Environmenf
and Finance. Studies in Fuzziness and Soft Computing. Heidelberg, New
York: Physica-Verlag, 2001.
[11] G. Sirbiladze, A. Sikharulidze and G. Korakhashvili, "Decision-making
Aiding Fuzzy Informational Systems in Investments. Part I –
Discrimination Analysis in Investment Projects”, Proceedings of Iv.
Javakhishvili Tbilisi State University. Applied Mathematics and
Computer Sciences, 353 (22-23), 2003, 77-94.
[12] G. Sirbiladze and T. Gachechiladze, "Restored fuzzy measures in expert
decision-making ”, Information Sciences, 169 (1/2), 2005, 71-95.
[13] G. Sirbiladze and A. Sikharulidze, "Weighted Fuzzy Averages in Fuzzy
Environment, Parts I, II”, International Journal of Uncertainty,
Fuzziness and Knowledge-Based Systems, 11(2), 2003, 139-157, 159-
172.
[14] G. Sirbiladze, "Decision Precising Technologies in Decision Making
Systems”, Plenary Speech. In: N. Mastorakis, M. Demiralp, I. Rudas, C.
A. Bulucea, L. Rogozea (Eds.), Proc.of the Applied Computing
Conference 2009, ACC '09, Vouliagmeni, Athens, Greece, 2009, pp. 27-
28.
[15] G. Sirbiladze, A. Sikharulidze and N. Sirbiladze, "Generalized Weighted
Fuzzy Expected Values in Uncertainty Environment”, In: L. A. Zadeh, J.
Kacprzyk, N. Mastorakis, A. Kuri-Morales, P. Borne, L. Kazovsky
(Eds.), Proc. 9th WSEAS Int. Conf. on Artificial Intelligence, Knowledge
Engineering and Data Bases, AIKED '10, University of Cambridge, UK,
2010, pp. 59-65.
[16] G. Sirbiladze, "Fuzzy dynamic programming problem for extremal
fuzzy dynamic systems”, In: W. A. Lodwick and J. Kacprzyk (Eds.)
Fuzzy Optimization: Recent Developments and Applications, Studies in
Fuzziness and Soft Computing, 254, Heidelberg: Physica-Verlag, 231-
270, 2010.
[17] G. Sirbiladze, "Fuzzy Identification Problem for Continuous Extremal
Fuzzy Dynamic System”, Fuzzy Optimization and Decision Making, 9
(3), 2010, 233-274.
[18] G. Sirbiladze, I. Khutsisvili and P. Dvalishvili, "Decision Precising
Fuzzy Technology to Evaluate the Credit Risks of Investment Projects”,
IEEE 10-th International Conference on Intelligent Systems Desigh and
Applications (ISDA 2010), Cairo, Egypt, 2010, 103-108.
[19] G.Sirbiladze, I. Khutsishvili and B. Ghvaberidze, "Multistage decisionmaking
fuzzy methodology for optimal investments based on experts’
evaluations”, European Journal of Operational Research, 232(1), 2014,
169–177.
[20] D. Wu, Y. Zhang, D. Wu and D. L. Olson, "Fuzzy multi-objective
programming for supplier selection and risk modeling: A possibility
approach”, European Journal of Operational Research, 200(3), 2010,
774-787
[21] R. R. Yager, "On the Evalution of Uncertain Courses of Action”, Fuzzy
Optimization and Decision Making, 1(1), 2002, 13-41.
[22] R. R.Yager, "Aggregation of ordinal information”, Fuzzy Optimization
and Decision Making, 6(3), 2007, 199-219.
[23] L. Yu, S. Wang and K. K. Lai, "An intelligent-agent-based fuzzy group
decision making model for financial multicriteria decision support: The
case of credit scoring”, European Journal of Operational Research,
195(3), 2009, 942-959.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:68114", author = "O. Badagadze and G. Sirbiladze and I. Khutsishvili", title = "Two Stage Fuzzy Methodology to Evaluate the Credit Risks of Investment Projects", abstract = "The work proposes a decision support methodology
for the credit risk minimization in selection of investment projects.
The methodology provides two stages of projects’ evaluation.
Preliminary selection of projects with minor credit risks is made
using the Expertons Method. The second stage makes ranking of
chosen projects using the Possibilistic Discrimination Analysis
Method. The latter is a new modification of a well-known Method of
Fuzzy Discrimination Analysis.
", keywords = "Expert valuations, expertons, investment project
risks, positive and negative discriminations, possibility distribution.", volume = "8", number = "10", pages = "1324-6", }
