• Subrata Jana Department of Mathematics, Jadavpur University, Kolkata, West Bengal, India
  • Bibhas Chandra Giri Department of Mathematics, Jadavpur University, Kolkata, West Bengal, India
  • Anirban Sarkar Department of Management and Marketing, West Bengal State University, Barasat, West Bengal, India
  • Chiranjibe Jana Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai 602105, Tamil Nadu, India
  • Željko Stević Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul 02841; Korea
  • Marko Radovanović Military Academy, University of Defence in Belgrade, Belgrade, Serbia



Financial Indices, Priority Selection, Multi-Criteria Decision-Making (MCDM), Triangular Fuzzy Number (TFN), Fuzzy Analytic Hierarchy Process (F-AHP)


By providing important indicators, financial indices help investors make educated judgements regarding their assets, much like vital sign monitors for the financial markets. The best way for investors to keep up with the market and make strategic adjustments is to keep an eye on these indexes. Researching the most important financial indexes for making educated investing decisions is, thus, quite relevant. Finding the most essential financial indices from an investing standpoint and assigning a weight to each of those indexes are the main goals of this research. A weighted score is derived by combining four financial indices in a Multi-Criteria Decision-Making (MCDM) technique. These objectives are then pursued. Triangular Fuzzy Numbers (TFNs) and the Fuzzy Analytic Hierarchy Process (F-AHP) are used to determine the weights of criteria in this technique. Using these methods together, the research hopes to provide a thorough analysis of the role that different financial indexes have in informing investment choices. This study emphasizes the paramount importance of considering the Price Earning to Growth (PEG) ratio when making investment decisions, followed by the Debt Equity Ratio. Price to Book Value and Dividend Yield, while relevant, carry comparatively less weightage in the overall assessment. Investors are advised to use these insights as a guideline in their financial analysis and decision-making processes.


Ala, A., Simic, V., Pamucar, D., & Jana, C. (2023). A Novel Neutrosophic-Based Multi-Objective Grey Wolf Optimizer for Ensuring the Security and Resilience of Sustainable Energy: A Case Study of Belgium. Sustainable Cities and Society.

Bajec, P., & Tuljak-Suban, D. (2019). A framework for detecting the proper multi-criteria decision-making method taking into account the characteristics of third-party logistics, the requirements of managers, and the type of input data. In Application of Decision Science in Business and Management. IntechOpen.

Baskaran, V., Madasamy, M., Kumar, S. P., & Sahana, S. V. (2023). Modeling the land suitability for agricultural utility in a semi-arid region of Tirunelveli district, South India using multi-criteria and geospatial approach. Modeling Earth Systems and Environment, 1-11.

Bobar, Z., Božanić, D., Đurić-Atanasievski, K., Pamučar, D.: (2020). Ranking and Assessment of the Efficiency of Social Media using the Fuzzy AHP-Z Number Model - Fuzzy MABAC, Acta Polytechnica Hungarica, 17(3), 43-70.

Božanić, D. I., Pamučar, D. S., & Karović, S. M. (2016). Hibridni model fuzzy AHP–MABAC za rangiranje potencijalnih lokacija za izradu maskirnih vezova. Vojnotehnički glasnik/Military Technical Courier, 64(3), 705-729.

Božanić, D., Pamučar, D., & Bojanić, D. (2015). Modification of the analytic hierarchy process (AHP) method using fuzzy logic: Fuzzy AHP approach as a support to the decision making process concerning engagement of the group for additional hindering. Serbian Journal of Management, 10(2), 151-171.

Bozanic, D., Tešić, D., Komazec, N., Marinković, D., & Puška, A. (2023). Interval fuzzy AHP method in risk assessment. Reports in Mechanical Engineering, 4(1), 131-140.

Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy sets and systems, 17(3), 233-247.

Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, 95(3), 649-655.

Chen, H., Huang, A. B., Peng, B., & Liu, Y. M. (2023). Evaluation of Post-Earthquake Geological Environment Carrying Capacity Based on AHP-GIS Coupled Analysis Method. Acadlore TTransactions on Geosciences, 2(1), 14-23.

Dabić-Miletić, S., & Raković, K. (2023). Ranking of autonomous alternatives for the realization of intralogistics activities in sustainable warehouse systems using the TOPSIS method. Spectrum of Engineering and Management Sciences, 1(1), 48-57.

Fattoruso, G., Barbati, M., Ishizaka, A. and Squillante, M. (2022). A hybrid AHPSort II and multi-objective portfolio selection method to support quality control in the automotive industry. Journal of the Operational Research Society, 1-16.

Fattoruso, G., Scognamiglio, S. and Violi, A. (2022). A New Dynamic and Perspective Parsimonious AHP Model for Improving Industrial Frameworks. Mathematics, 10(17).

Gallizo, J. L., Jiménez, F., & Salvador, M. (2002). Adjusting financial ratios: a Bayesian analysis of the Spanish manufacturing sector. Omega, 30(3), 185-195.

Ghorui, N., Ghosh, A., Mondal, S. P., Kumari, S., Jana, S., & Das, A. (2021). Evaluation of performance for School Teacher Recruitment using MCDM techniques with Interval Data. Multicultural Education, 7(5).

Ghosh, A. (2021). Analyzing Efficiency of Indian Life Insurance Companies using DEA and SEM. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(12), 3897-3919.

Ghosh, A., Jana, S. (2017). Best Indian Information Technology company based on Financial Ratios analysis using VIKOR method. Arthvati-Journal of Economics, 3 (7), 89-100.

Ghunaim, H., & Dichter, J. (2019). Applying the FAHP to improve the performance evaluation reliability of software defect classifiers. IEEE Access, 7, 62794-62804.

Hadžikadunić, A., Stević, Ž., Badi, I., & Roso, V. (2023). Evaluating the Logistics Performance Index of European Union Countries: An Integrated Multi-Criteria Decision-Making Approach Utilizing the Bonferroni Operator. International Journal of Knowledge and Innovation Studies, 1(1), 44-59.

Hangshenas, S., Özçelik, Y., Mikaeil, R., & Moghaddam, S. (2017). Ranking and Assesment of tunneling projects risks using fuzzy MCDM (Case Study: Toyserkan Doolayi Tunnel).

Hsieh, H. N., Chen, J. F., & Do, Q. H. (2015). Applying TRIZ and fuzzy AHP based on lean production to develop an innovative design of a new shape for machine tools. Information, 6(1), 89-110.

Jana, C. (2021). Multiple attribute group decision-making method based on extended bipolar fuzzy MABAC approach. Computational and Applied Mathematics, 40(6), 227.

Jana, C., Dobrodolac, M., Simic, V., Pal, M., Sarkar, B., & Stević, Ž. (2023). Evaluation of sustainable strategies for urban parcel delivery: Linguistic q-rung orthopair fuzzy Choquet integral approach. Engineering Applications of Artificial Intelligence, 126.

Jana, C., Mohamadghasemi, A., Pal, M., & Martinez, L. (2023). An improvement to the interval type-2 fuzzy VIKOR method. Knowledge-Based Systems, 280.

Jana, C., Simic, V., Pal, M., Sarkar, B., & Pamucar, D. (2024). Hybrid multi-criteria decision-making method with a bipolar fuzzy approach and its applications to economic condition analysis. Engineering Applications of Artificial Intelligence, 132.

Jana, S., Basu, S (2021). Ranking of Top 20 Pharmaceutical Companies in India using TOPSIS. Empirical Economics Letters, ISSN 1681 8997, Special Issue 3.

Jana, S., Maji, B., Sarkar, A. (2019). Linear Programming Approach for Portfolio Review. Parishodh Journal,8(XI), 692-702.

Johnson, H., Isaksson, L., & Fiedler, M. (2006, April). SF Wu. A decision system for adequate authentication. In Proceedings of the International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies (ICNICONSMCL’06), Washington, DC, USA.

Khan, A. A., Mashat, D. S., & Dong, K. (2024). Evaluating Sustainable Urban Development Strategies through Spherical CRITIC-WASPAS Analysis. Journal of Urban Development and Management, 3(1), 1-17.

Krstic, M., Tadic, S., & Agnusdei, L. (2023). Evaluating governance models in intermodal terminal operations: A hybrid grey MCDM approach. Journal of Intelligent Management Decision, 2(4), 179-191.

Kumar, R. D., &Nagarajan, V. (2021). Implementation and performance measure of fuzzy AHP for resource allocation in 5G. Fluctuation and Noise Letters, 20(02), 2150020.

Kung, J. Y., Chuang, T. N., &Ky, C. M. (2011, June). A fuzzy MCDM method to select the best company based on financial report analysis. In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011) (pp. 2013-2017). IEEE.

Laitinen, E. K. (2006). Financial statement data in assessing the future potential of a technology firm: The case of Nokia. International Review of Financial Analysis, 15(3), 256-286.

Low, C., & Hsueh Chen, Y. (2012). Criteria for the evaluation of a cloud-based hospital information system outsourcing provider. Journal of medical systems, 36, 3543-3553.

Modibbo, U. M., Hassan, M., Ahmed, A. and Ali, I. (2022). Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS.” Management Decision 60 (3), 806- 836.

Nandi, S., Granata, G., Jana, S., Ghorui, N., Mondal, S. P., &Bhaumik, M. (2023). Evaluation of the treatment options for COVID-19 patients using generalized hesitant fuzzy-multi criteria decision making techniques. Socio-Economic Planning Sciences.

Nazzal, D., Mustafa, D., Halabi, E., Gnimat, S., & Gayada, S. (2019). Evaluation of types, stages and treatment of breast cancer among Palestinian women. Palestinian Medical and Pharmaceutical Journal (Pal. Med. Pharm. J.), 5(1), 35-40.

Öcal, M. E., Oral, E. L., Erdis, E., &Vural, G. (2007). Industry financial ratios—application of factor analysis in Turkish construction industry. Building and environment, 42(1), 385-392.

Onay, A., Karamaşa, Ç., & Saraç, B. (2016). Application of Fuzzy AHP in Selection of Accounting Elective Courses in Undergraduate and Graduate Level. Journal of Accounting Finance and Auditing Studies, 2(4), 20-42.

Petrović, N., Živanović, T., & Mihajlović, J. (2023). Evaluating the annual operational efficiency of passenger and freight road transport in Serbia through entropy and TOPSIS methods. Journal of Engoneering Management and Systems Engineering, 2(4), 204-211.

Prajapati, D., Daultani, Y., Cheikhrouhou, N., & Pratap, S. (2020). Identification and ranking of key factors impacting efficiency of Indian shipping logistics sector. Opsearch, 57, 765-786.

Saaty, T. (1980, November). The analytic hierarchy process (AHP) for decision making. In Kobe, Japan ,1, p. 69.

Seruffo, M., Frances, C., Santana, A., & Vijaykumar, N. (2012). Heuristic algorithm based on multicriteria analysis for selection of first mile access in standard integrated services digital broadcasting terrestrial. IET Communications, 6(17), 2933-2940.

Sharma, A., Hussain, V. M. S., Kumar, P. A., & Pandit, M. (2023). Prioritization of forging die design criteria based on failure analysis using fuzzy analytic hierarchy process (FAHP). Materials Today: Proceedings, 80, 925-932.

Shekar, P. R., & Mathew, A. (2023). Integrated assessment of groundwater potential zones and artificial recharge sites using GIS and Fuzzy-AHP: a case study in Peddavagu watershed, India. Environmental Monitoring and Assessment, 195(7).

Shiue, W., Li, S. T., & Chen, K. J. (2008). A frame knowledge system for managing financial decision knowledge. Expert Systems with Applications, 35(3), 1068-1079.

Stevic, Z., N. Mujakovic, A. Goli, and S. Moslem. Selection of logistics distribution channels for final product delivery: FUCOM-MARCOS model. Journal of Intelligent Management Decision 2 (4), 172-178.

Sun, J., & Li, H. (2009). Financial distress prediction based on serial combination of multiple classifiers. Expert Systems with Applications, 36(4), 8659-8666.

Taletović, M. (2023). Application of Multi-Criteria Decision-Making Methods in Warehouse: A Brief Review. Spectrum of Engineering and Management Sciences, 1(1), 25-37.

Van Laarhoven, P. J., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy sets and Systems, 11(1-3), 229-241.

Wang, Y. J., & Lee, H. S. (2008). A clustering method to identify representative financial ratios. Information Sciences, 178(4), 1087-1097.

Xidonas, P., Mavrotas, G., & Psarras, J. (2009). A multicriteria methodology for equity selection using financial analysis. Computers & operations research, 36(12), 3187-3203.

Yang, C. C., & Chen, B. S. (2004). Key quality performance evaluation using fuzzy AHP. Journal of the Chinese Institute of Industrial Engineers, 21(6), 543-550.

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.

Zangoueinezhad, A., & Moshabaki, A. (2011). Measuring university performance using a knowledge-based balanced scorecard. International Journal of Productivity and Performance Management, 60(8), 824-843.

Zavadskas, E. K., Turskis, Z., Stević, Ž., & Mardani, A. (2020). Modelling procedure for the selection of steel pipes supplier by applying fuzzy AHP method. Operational Research in Engineering Sciences: Theory and Applications, 3(2), 39-53.




How to Cite