Aлгоритми за процену квалитативних и квантитативних ризика кредитирања малих и средњих предузећа засновани на фази рачуну

Ključne reči: ризик, процена, фази мере, фази интеграл, фази број

Sažetak


Данас кризни услови у привреди и финансијама захтевају квалитетну процену ризика. У чланку аутори предлажу два алгоритма за процену ризика кредитирања пројеката (РКП) за мала и средња предузећа. За процену квалитативних РКП-а, предложили смо употребу хијерархијског система критеријума, у коме се важност критеријума описује коришћењем Сугено фази мере, а генерализована процена квалитативног ризика се израчунава коришћењем Сугено фази интеграла. Да бисмо проценили квантитативне РКП, предложили смо да се користе карактеристике фази бројева који описују критеријуме ефективности пројекта и имају произвољни облик функције припадности. Поред тога, за описивање квантитативних ризика, предложили смо да се користи функција ризика фази броја, која одражава не само величину могућих губитака, већ и могућност њиховог настанка. Ово вам омогућава да свеобухватно и објективно процените ниво ризика. Ове алгоритме смо демонстрирали и дискутовали на примеру припреме података за доношење одлуке о кредитирању пројекта за производњу кукурузног сирупа у Украјини.

Reference

Appadoo, S.S., Bhatt, S.K., & Bector, C.R. (2008). Application of possibility theory to investment decisions. Fuzzy Optimization and Decision Making, 7 (1), 35-57.

Atra, R.J., & Thomas, R. (2009). Developing an Automated Discounted Cash Flow Model. Thomas, R., Gup, B.E. (eds), The Valuation Handbook, John Wiley & Sons, Inc. 108-134.

Averkin, A.N., Batyrshin, I.Z., Blishun, A.F., Silov, V.B., & Tarasov, V.B. (1986). Fuzzy Sets in Control Models and Artificial Intelligence (in Russian). Pospelov, D.A. (ed). The science, Moscow.

Ayyub, B.M., & Klir, G.J. (2006). Uncertainty Modeling and Analysis in Engineering and the Sciences (1st ed.). Chapman and Hall/CRC.

Bede, B., & Fodor, J. (2006). Product Type Operations between Fuzzy Numbers and their Applications in Geology. Acta Polytechnica Hungarica, 3 (1), 123-139.

Bodjanova, S. (2005). Median value and median interval of a fuzzy number. Information Sciences, 172(1-2), 73–89.

Choquet, G. (1954). Theory of capacities. Annales de l’Institut Fourier, 5, 131–295.

Frei, D., & Ruloff, D. (1988). The methodology of political risk assessment: An overview. World Futures: Journal of General Evolution, 25 (1-2), 1-24.

Fuzzy for Excel. Available at: https://www.dropbox.com/s/2qre4sfuo3jawie/Fuzzy%20for%20Excel%2064bit.zip?dl=0

Gejirifu, D., Zhongfu, T., Menglu, L., Lilin H., Qiang W., & Huanhuan L. (2019). A credit risk evaluation based on intuitionistic fuzzy set theory for the sustainable development of electricity retailing companies in China. Energy Science & Engineering, 7 (6), 2825-2841.

Ghatasheh, N. (2014). Business analytics using random forest trees for credit risk prediction: a comparison study. International Journal of Advanced Science and Technology, 72, 19-30.

Liu, H., & Sizong, G.U.O. (2007). Equality and Identity of Fuzzy Numbers and Fuzzy Arithmetic with Equality Constraints. In International Conference on Intelligent Systems and Knowledge Engineering 2007, Atlantis Press. 334-339.

Harrington, E.C. (1965). The Desirability Function. Industrial Quality Control, 21(10), 494 – 498.

Jaya Y, B.J., & Tamilselvi, J.J. (2018). Fuzzy multi-criteria random seed and cutoff point approach for credit risk assessment. Journal of Theoretical & Applied Information Technology, 96 (4), 1150-1163.

Kaufmann, S., Condoravdi, C., & Harizanov, V. (2006) Formal approaches to modality. Frawley, W. (Ed.). The Expression of Modality. Mouton de Gruyter. Berlin, New York. 71-106.

Kengatharan, L. (2016). Capital budgeting theory and practice: a review and agenda for future research. Research Journal of Finance and Accounting, 7 (1), 1-22.

Keshk, A.M., Maarouf, I., & Annany, Y. (2018). Special studies in management of construction project risks, risk concept, plan building, risk quantitative and qualitative analysis, risk response strategies. Alexandria engineering journal, 57 (4), 3179-3187.

Klir, G.J. (1997). Fuzzy arithmetic with requisite constraints. Fuzzy Sets and Systems, 9 (2), 165-175. Available at: https://doi.org/10.1016/S0165-0114(97)00138-3.

Kosheleva O., Cabrera S.D., Gibson G.A., & Koshelev M. (1997). Fast implementations of fuzzy arithmetic operations using fast Fourier transform (FFT). Fuzzy Sets and Systems, 91 (2), 269-277.

Lesage, C. (2001). Discounted cash-flows analysis: An interactive fuzzy arithmetic approach. European Journal of Economic and Social Systems, 15 (2), 49-68.

Liu, H., & Guo, S. (2007). Equality and Identity of Fuzzy Numbers and Fuzzy Arithmetic with Equality Constraints. Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007). 334-339.

Li, Y. (2015). Study on the Personal Credit Risk Evaluation based on Improved Fuzzy AHP Comprehensive Evaluation Method. 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer, Atlantis Press, 76-79.

Łyczkowska-Hanćkowiak, A. (2020). On Application Oriented Fuzzy Numbers for Imprecise Investment Recommendations. Symmetry, 12 (10), 1672.

Mareš, M. (1997). Weak arithmetics of fuzzy numbers. Fuzzy Sets and Systems, 91 (2), 143-153.

Namvar, A., & Naderpour, M. (2018). Handling uncertainty in social lending credit risk prediction with a Choquet fuzzy integral model. 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8.

Pisz, I., Chwastyk, A., & Łapuńka, I. (2019). Assessing the profitability of investment projects using ordered fuzzy numbers. Scientific Journal of Logistics, 15 (3), 377-389.

Purdy, G. (2010). ISO 31000: 2009–setting a new standard for risk management. Risk Analysis: An International Journal, 30 (6), 881-886.

Roy, A.D. (1952). Safety-first and the holding of assets. Econometrics, 20 (3), 431–449.

Saaty, T., & Kearns, K. (1985). Analytical planning: the organization of systems. International series in modern applied mathematics and computer science, 7. Pergamon Press.

Sharpe, W.F. (1966). Mutual fund performance. The Journal of business, 39 (1), 119-138.

Sirbiladze, G., Khutsishvili, I., & Dvalishvili, P. (2010). Decision precising fuzzy technology to evaluate the credit risks of investment projects. 10th International Conference on Intelligent Systems Design and Applications, 103-108.

Stefanini, L., Sorini, L., & Guerra, M.L. (2008). Fuzzy Numbers and Fuzzy Arithmetic. In Pedrycz, W., Skowron, A., & Kreinovich V. (eds). Handbook of Granular Computing, 249-284.

Sugeno, M. (1972). Fuzzy Measure and Fuzzy Integral. Transaction of the Society of Instrument and Control Engineers, 8 (2), 218-226.

Sveshnikov, S., & Bocharnikov, V. (2022). Computational Algorithm and Tools of Fuzzy Arithmetic Based on the Principle of Maximum Entropy. Research Article, preprint. Retrieved from https://doi.org/10.21203/rs.3.rs-1254409/v1.

Takahagi, E. (2000). On identification methods of λ-fuzzy measures using weights and λ. Japan Fuzzy Society Journal, 12 (5), 665-676.

Whelan, J., Msefer, K., & Chung, C.V. (2001). Economic supply & demand. MIT, Cambridge Mass.

Wnuk-Pel, T. (2014). The Practice and Factors Determining the Selection of Capital Budgeting Methods – Evidence from the Field. Procedia - Social and Behavioral Sciences, 156, 612-616.

Wójcicka-Wójtowicz, A., & Piasecki, K. (2021). Application of the Oriented Fuzzy Numbers in Credit Risk Assessment. Mathematics, 9 (5). 535.

Zadeh, L.A. (1975). The Concept of linguistic variable and its applications to approximate reasoning. Information Sciences, 8 (4), 301-357.

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