Borsa İstanbul'da Pandemi Dönemindeki Uzun Vadeli İHA Performansına İlişkin Karşılaştırmalı Bir ÇKKA Uygulaması

Year 2023, Volume: 8 Issue: 20, 269 - 293, 27.02.2023

Orhan Emre Elma

https://doi.org/10.25204/iktisad.1242437

Cited By: 3

Abstract

Bu çalışmanın amacı, halka arzların uzun vadeli performans analizlerini karşılaştırmalı bir analiz sistemiyle yaparak finansal karar vericilere bir referans yol haritası sunmaktır. Karmaşık cevapları olan problemlerde çok kriterli karar analizi (ÇKKA) yöntemleri kullanılmaktadır. 2020 yılının ilk çeyreğinde tüm dünyaya yayılan pandemi, sermaye piyasalarında kısa süreli bir şok etkisi yaratsa da sermaye piyasaları bu şoku yeni yatırımcılarla atlatmıştır. Pandemi öncesi Borsa İstanbul'daki hissedar sayısı 1,3 milyon iken bu sayı sonrasında 3,3 milyonu geçmiştir. Bu sayının artması aynı zamanda finansal karar vericilerin sayısının da artması anlamına gelmektedir. Bu araştırmada, Borsa İstanbul'da pandemi öncesi gerçekleşen 49 adet ilk halka arzın uzun dönem performansı karşılaştırmalı ÇKKA perspektifiyle incelenmektedir. Bu amaçla CRITIC ağırlıklandırma tekniği ile ARAS, MOORA, TOPSIS, COPRAS ve ELECTRE III yöntemlerinin kullanıldığı çalışmada pandemi sürecindeki 10 dönem incelenmiştir. Halka arz alanında yapılmış en kapsamlı ÇKKA çalışması olan araştırma sonucunda, analiz edilen diğer 4 yönteme göre üstün sonuçlar ürettiği için MOORA yöntemi finansal karar vericilere önerilmiştir.

Keywords

ÇKKV, Sermaye Piyasaları, Uzun Dönemli Performans, İlk Halka Arz

A Comparative MCDA Application on The Long-Term Performance of IPOs During the Pandemic on Borsa Istanbul

Abstract

The aim of the study is to help financial decision makers by making long-term performance analysis of initial public offerings with a comparative analysis perspective. Multi-criteria decision analysis (MCDA) methods are used in problems with complex answers. The pandemic, which spreads throughout the world in the first quarter of 2020, created a short-term shock effect in the capital markets, but capital markets survived this shock with new investors. While the number of shareholders in Borsa Istanbul was 1.3 million before the pandemic, this number exceeded 3.3 million afterwards. An increase in this number also means an increase in the number of financial decision makers. At this research, the long-term performance of 49 initial public offerings, which took place in Borsa Istanbul before the pandemic is analyzed with a comparative MCDA perspective. To that end, the study, in which CRITIC weighting technique and ARAS, MOORA, TOPSIS, COPRAS and ELECTRE III methods were used, examined 10 periods during the pandemic process. As a result of the research, which is the most comprehensive MCDA study in the field of IPOs, the MOORA method has been recommended to financial decision makers because it produced superior results compared to other 4 methods analyzed.

Keywords

Capital Markets, MCDA, Long-Term Performance, IPO

References

• Abdi, Y., Li, X., and Càmara-Turull, X. (2022). Exploring the impact of sustainability (ESG) disclosure on firm value and financial performance (FP) in airline industry: the moderating role of size and age. Environment, Development and Sustainability, 24(4), 5052-5079.
• Ahmad, W., Ahmed, T. and Shabbir, G. (2015). Determinants of textile firms’ profitability in Pakistan. Forman Journal of Economic Studies, 11(1), 87-101.
• Al-Homaidi, E. A., Tabash, M. I., Farhan, N. H., and Almaqtari, F. A. (2018). Bank-specific and macro-economic determinants of profitability of Indian commercial banks: A panel data approach. Cogent Economics & Finance, 6(1): 1548072.
• Artikis, P. G. (2008). Wealth Added Financial Management Research. Mibes E-book. Ashayeri, J. and Rongen, J. M. (1997). Central distribution in Europe: A multi-criteria approach to location selection. The International Journal of Logistics Management, 8(1), 97-109.
• Augusto, M., Lisboa, J., Yasin, M., and Figueira, J. R. (2008). Benchmarking in a multiple criteria performance context: An application and a conceptual framework. European Journal of Operational Research, 184(1), 244-254.
• Azimi, F. A., Jalali, A. A., and Farahi, A. (2012). Comparison of multiple criterion decision making methods for evaluation Parsian banks e-readiness for ECRM implementation. Australian Journal of Basic and Applied Sciences, 6(9), 251-263.
• Balezentis, A., and Balezentis, T. (2011a). Framework of strategic management model for strategy Europe 2020: Diachronic analysis and proposed guidelines. Inžinerinė ekonomika-Engineering Economics, 22(3), 271–282.
• Balezentis, A., Valkauskas, R., and Balezentis, T. (2010). Evaluating situation of Lithuania in the European Union: structural indicators and MULTIMOORA method. Technological and Economic Development of Economy, 16(4), 578–602.
• Balezentis, T. and Streimikiene, D. (2017). Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation. Applied Energy, 185, 862-871. https://doi.org/10.1016/j.apenergy.2016.10.085.
• Balezentis, T., and Balezentis, A. (2011b). A multi-criteria assessment of relative farming efficiency in the European Union Member States. Žemės ūkio mokslai, 18(3), 125–135.
• Baydaş, M., and Elma, O. E. (2021). An objective criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul. Decision Making: Applications in Management and Engineering, 4(2), 257–279. https://doi.org/10.31181/dmame210402257b
• Baydaş, M., Elma, O. E., and Pamučar, D. (2022). Exploring the specific capacity of different multi criteria decision making approaches under uncertainty using data from financial markets. Expert Systems with Applications, 197, 116755. https://doi.org/10.1016/j.eswa.2022.116755
• Brauers, W. K. M. (2012). Project management for a country with multiple objectives. Czech Economic Review, 6(1), 80–101.
• Brauers, W. K. M. (2013). Multi-objective seaport planning by MOORA decision making. Annals of Operations Research, 206(1), 39-58.
• Brauers, W. K. M. and Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and economic development of economy, 16(1), 5-24.
• Brauers, W. K. M., and Zavadskas, E. K. (2012). Robustness of MULTIMOORA: A method for multi-objective optimization. Informatica, 23(1), 1–25.
• Brauers, W. K. M., Zavadskas, E. K., Peldschus, F., and Turskis, Z. (2008). Multi‐objective decision‐making for road design. Transport, 23(3), 183-193.
• Brauers, W.K.M. (2004). Optimization methods for a stakeholder society, a revolution in economic thinking by multi-objective optimization. Boston: Kluwer Academic Publishers.
• Bülbül, S., and Köse, A. (2011). Türk Gıda Şirketlerinin Finansal Performansının Çok Amaçlı Karar Verme Yöntemleriyle Değerlendirilmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 25, 71-97.
• Chatterjee, P., and Chakraborty, S. (2012). Material selection using preferential ranking methods. Materials & Design, 35, 384–393.
• Cho, S. J., Chung, C. Y., and Young, J. (2019). Study on the Relationship between CSR and Financial Performance. Sustainability, 11(2), 343.
• Conkar, K., Elitas, C., and Atar, G. (2011). İMKB Kurumsal Yönetim Endeksi'ndeki (XKURY) Firmaların Finansal Performanslarının TOPSIS Yöntemi ile Ölçümü ve Kurumsal Yönetim Notu ile Analizi. İstanbul Üniversitesi İktisat Fakültesi Mecmuası, 61(1), 81-115.
• Dahooie, J. H., Abadi, E. B. J., Vanaki, A. S. and Firoozfar, H. R. (2018). Competency-based IT personnel selection using a hybrid SWARA and ARAS-G methodology. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(1), 5-16. https://doi.org/10.1002/hfm.20713.
• Dahooie, J. H., Zavadskas, E. K., Vanaki, A. S., Firoozfar, H. R., Lari, M. and Turskis, Z. (2019). A new evaluation model for corporate financial performance using integrated CCSD and FCM-ARAS approach. Economic Research-Ekonomska Istrazivanja, 32(1), 1088-1113. https://doi.org/10.1080/1331677X.2019.1613250.
• Ecer, Fatih (2019). A Multi-criteria Approach Towards Assessing Corporate Sustainability Performances of Privately-owned Banks: Entropy-ARAS Integrated Model. Eskisehir Osmangazi Universitesi Iibf Dergisi-Eskisehir Osmangazi University Journal Of Economics And Administrative Sciences, 14(2), 365-390. https://doi.org/10.17153/oguiibf.470336.
• Elking, I., Paraskevas, J. P., Grimm, C., Corsi, T. and Steven, A. (2017). Financial dependence, lean inventory strategy, and firm performance. Journal of Supply Chain Management, 53(2), 22-38.
• Ergül, N. (2014). BİST-Turizm sektöründeki şirketlerin finansal performans analizi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 4(1), 325-340.
• Ganda, F. (2018). The effect of carbon performance on corporate financial performance in a growing economy. Social Responsibility Journal, 14(4), 895-916.
• Ghadikolaei, A. S. and Esbouei, S. K. (2014). Integrating FAHP and Fuzzy ARAS for evaluating financial performance. Boletim Sociedade Paranaense De Matematica, 32(2), 163-174. https://doi.org/10.5269/bspm.v32i2.21.378.
• Ghadikolaei, A. S., Esbouei, S. K. and Antucheviciene, J. (2014). Applying Fuzzy MCDM For Financial Performance Evaluation of Iranian Companies. Technological and Economic Development of Economy, 20(2), 274-291. https://doi.org/10.3846/20294913.2014.913274.
• Ghenai, C., Albawab, M. and Bettayeb, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580-597. https://doi.org/10.1016/j.renene.2019.06.157.
• Halkos, G.E. and Tzeremes, N.G. (2002). Industry performance evaluation with the use of financial ratios: An application of bootstrapped DEA. Expert System with Applications, 39, 5872–5880.
• Jahanshahloo, G. R., Lotfi, F. H. and Izadikhah, M. (2006). An algorithmic method to extend TOPSIS for decision-making problems with interval data. Applied mathematics and computation, 175(2), 1375-1384.
• Jana, T. K., Bairagi, B., Paul, S., Sarkar, B., and Saha, J. (2013). Dynamic schedule execution in an agent based holonic manufacturing system. Journal of Manufacturing Systems, 32(4), 801–816.
• Kaklauskas, A., Zavadskas, E. K., Raslanas, S., Ginevicius, R., Komka, A., and Malinauskas, P. (2006). Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: A Lithuanian case. Energy and Buildings, 38(5), 454–462.
• Kalakkar, S. (2012). Key factors in determining the financial performance of the Indian banking sector. Available at SSRN 2121351.
• Karabasevic, D., Zavadskas, E. K., Turskis, Z. and Stanujkic, D. (2016). The Framework for the Selection of Personnel Based on the SWARA and ARAS Methods Under Uncertainties. Informatica, 27(1), 49-65. https://doi.org/10.15388/Informatica.2016.76.
• Kersuliene, V. and Turskis, Z. (2011). Integrated Fuzzy Multiple-Criteria Decision-Making Model for Architect Selection. Technological and Economic Development of Economy, 17(4), 645-666. https://doi.org/10.3846/20294913.2011.635718.
• Kizielewicz, B., Shekhovtsov, A., Sałabun, W., and Piegat, A. (2021). Decision-Making Problems with Local Extremes: Comparative Study Case. Poster session presentation at the meeting of International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland.
• Kumaran, S. (2022). Financial performance index of IPO firms using VIKOR-CRITIC techniques. Finance Research Letters, 47, 102542.
• Kumaraswamy, M., and Ramaswamy, R. (2016). Performance evaluation of software projects using criteria importance through inter–criteria correlation technique. International Journal of Soft Computing and Software Engineering, 6(3), 28-36.
• Lee, K. H., Cin, B. C., and Lee, E. Y. (2016). Environmental responsibility and firm performance: The application of an environmental, social and governance model. Business Strategy and the Environment, 25(1), 40-53.
• Li, H., Adeli, H., Sun, J. and Han, J. G. (2011). Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction. Computers & Operations Research, 38(2), 409-419.
• Makan, L. T. and Kabra, K. C. (2021). Carbon Emission Reduction and Financial Performance in an Emerging Market: Empirical Study of Indian Firms. Indonesian Journal of Sustainability Accounting and Management, 5(1), 23-32.
• Matic, B., Jovanovic, S. D., Dillip K., Zavadskas, E. K., Stevic, Z., Sremac, S. and Marinkovic, M. (2019). A New Hybrid MCDM Model: Sustainable Supplier Selection in a Construction Company. Symmetry-Basel, 11(3), 353. https://doi.org/10.3390/sym11030353.
• Medineckiene, M., Zavadskas, E. K., Bjork, F., and Turskis, Z. (2015). Multi-criteria decision-making system for sustainable building assessment/certification. Archives Of Civil And Mechanical Engineering, 15(1), 11-18. https://doi.org/10.1016/j.acme.2014.09.001.
• Miralles-Quiros, M. M., Miralles-Quiros, J. L., and Valente Gonçalves, L. M. (2018). The value relevance of environmental, social, and governance performance: The Brazilian case. Sustainability, 10(3), 574.
• Miroshnychenko, I., Barontini, R., and Testa, F. (2017). Green practices and financial performance: A global outlook. Journal of Cleaner Production, 147, 340-351.
• Naz, F., Ijaz, F., and Naqvi, F. (2016). Financial performance of firms: evidence from Pakistan cement industry. Journal of Teaching and Education, 5(01), 81-94.
• Oliveira, R. M., Chaves, A. A., and Lorena, L. A. N. (2017). A comparison of two hybrid methods for constrained clustering problems. Applied Soft Computing, 54, 256-266.
• Ortiz‐de‐Mandojana, N., and Bansal, P. (2016). The long‐term benefits of organizational resilience through sustainable business practices. Strategic Management Journal, 37(8), 1615-1631.
• Petrovic, G., Mihajlovic, J., Cojbasic, Z., Madic, M. and Marinkovic, D. (2019). Comparison Of Three Fuzzy MCDM Methods For Solving The Supplier Selection Problem. Facta Universitatis-Series Mechanical Engineering, 17(3), 455-469. https://doi.org/10.22190/FUME190420039P.
• Popovic, G., Stanujkic, D., and Stojanovic, S. (2012). Investment project selection by applying copras method and imprecise data. Serbian Journal of Management, 7(2), 257–269.
• Qiu, Y., Shaukat, A., and Tharyan, R. (2016). Environmental and social disclosures: Link with corporate financial performance. The British Accounting Review, 48(1), 102-116.
• Rabbani, A., Zamani, M., Yazdani-Chamzini, A., and Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Systems with Applications, 41(16), 7316–7327.
• Rao, S. H., Kalvakolanu, S. and Chakraborty, C. (2021). Integration of ARAS and MOORA MCDM Techniques for Measuring the Performance of Private Sector Banks in India. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 29, 279-295. https://doi.org/10.1142/S0218488521400158.
• Reddy, N. R., Rajesh, M., and Reddy, T. N. (2011). Valuation through EVA and traditional measures an empirical study. International Journal of Trade, Economics and Finance, 2(1), 19.
• Roy, B. (1990). The outranking approach and the foundations of ELECTRE methods. In Readings in multiple criteria decision aid, 155-183. Springer: Berlin, Heidelberg.
• Saeed, R. B. A., and Badar, R. (2013). Impact of capital structure on performance empirical evidence from sugar sector of Pakistan. European Journal of Business and Management, 5(5), 78-86.
• Seçme, N. Y., Bayrakdaroğlu, A., and Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Expert systems with applications, 36(9), 11699-11709. https://doi.org/10.1016/j.eswa.2009.03.013
• Soba, M., Akcanli, F., and Erem, I. (2012). İMKB’ye kayıtlı seçilmiş işletmelere yönelik etkinlik ölçümü ve performans değerlendirmesi: Veri zarflama analizi ve TOPSIS uygulaması. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (27), 229-243.
• Stankeviciene, J., and Sviderske, T. (2012). Country risk assessment based on MULTIMOORA. In The 7th international scientific conference Business and Management, 530–536.
• Tan, C. (2011). A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS. Expert Systems with Applications, 38(4), 3023-3033.
• Topaloğlu, E. E. (2014). Finansal Krizlerin BIST Metal Eşya, Makina Endeksi’nde Faaliyet Gösteren Firmaların Finansal Performanslarına Etkisinin TOPSIS Yöntemi ile Ölçülmesi. Yönetim ve Ekonomi Araştırmaları Dergisi, 12(22), 286-305. https://doi.org/10.11611/JMER230.
• Turskis, Z. and Zavadskas, E. K. (2010). A New Fuzzy Additive Ratio Assessment Method (ARAS-F). Case Study: The Analysis of Fuzzy Multiple Criteria in Order to Select the Logistic Centers Location. Transport, 25(4), 423-432. https://doi.org/10.3846/transport.2010.52.
• Uzsilaityte, L., and Martinaitis, V. (2010). Search for optimal solution of public building renovation in terms of life cycle. Journal of Environmental Engineering and Landscape Management, 18(2), 102–110.
• Visalakshmi, S., Lakshmi, P., Shama, M. S. and Vijayakumar, K. (2015). An integrated fuzzy DEMATEL-TOPSIS approach for financial performance evaluation of GREENEX industries. International Journal of Operational Research, 23(3), 340-362.
• Wang, J. (2008). Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan. Expert Systems with Applications, 34(3), 1837-1845. https://doi.org/10.1016/j.eswa.2007.02.029.
• Wang, Z. and Rangaiah, G. P. (2017). Application and analysis of methods for selecting an optimal solution from the Pareto-Optimal front obtained by multi-objective optimization. Industrial & Engineering Chemistry Research, 56, 560–574. https://doi.org/10.1021/acs.iecr.6b03453.
• Wu, M. C. and Chen, T. Y. (2011). The ELECTRE multicriteria analysis approach based on Atanassov’s intuitionistic fuzzy sets. Expert Systems with Applications, 38(10), 12318-12327.
• Xie, J., Nozawa, W., Yagi, M., Fujii, H., and Managi, S. (2019). Do environmental, social, and governance activities improve corporate financial performance?. Business Strategy and the Environment, 28(2), 286-300.
• Yaakob, A. M., and Gegov, A. (2016). Interactive TOPSIS based group decision making methodology using Z-Numbers. International Journal of Computational Intelligence Systems, 9(2), 311–324. https://doi.org/10.1080/18756891.2016.1150003.
• Yalçın, N. and Ünlü, U. (2018). A multi-criteria performance analysis of Initial Public Offering (IPO) firms using CRITIC and VIKOR methods. Technological and Economic development of Economy, 24(2), 534-560.
• Yayar, R., and Baykara, H. V. (2012). An Implementation upon Efficiency and Productivity of Participation Banks with TOPSIS Method. Business and Economics Research Journal, 3(4), 21.
• Zaidan, B. B., Zaidan, A. A., Abdul Karim, H., and Ahmad, N. N. (2017). A new approach based on multi-dimensional evaluation and benchmarking for data hiding techniques. International Journal of Information Technology & Decision Making, 16, 1–42. https://doi.org/10.1142/S0219622017500183.
• Zamani, L., Beegam, R. and Borzoian, S. (2014). Portfolio selection using Data Envelopment Analysis (DEA): A case of select Indian investment companies. International Journal of Current Research and Academic Review, 2(4), 50-55.
• Zavadskas, E. K. and Turskis, Z. (2010). A New Additive Ratio Assessment (ARAS) Method In Multicriteria Decision-Making. Technological and Economic Development of Economy, 16(2), 159-172. https://doi.org/10.3846/tede.2010.10.
• Zavadskas, E. K., Turskis, Z. and Bagocius, V. (2015). Multi-criteria selection of a deep-water port in the Eastern Baltic Sea. Applied Soft Computing, 26, 180-192. https://doi.org/10.1016/j.asoc.2014.09.019.
• Zavadskas, E. K., Turskis, Z., and Vilutiene, T. (2010). Multiple criteria analysis of foundation instalment alternatives by applying Additive Ratio Assessment (ARAS) method. Archives of Civil and Mechanical Engineering, 10(3), 123-141. https://doi.org/10.1016/S1644-9665(12)60141-1.
• Zavadskas, E. K., Vainiunas, P., Turskis, Z. and Tamosaitiene, J. (2012). Multiple Criteria Decision Support System for assessment of projects managers in construction. International Journal of Information Technology & Decision Making, 11(2), 501-520. https://doi.org/10.1142/S0219622012400135.
• Zhao, X., and Murrell, A. J. (2016). Revisiting the corporate social performance‐financial performance link: A replication of Waddock and Graves. Strategic Management Journal, 37(11), 2378-2388.
• Zolfani, S. H., and Bahrami, M. (2014). Investment prioritizing in high tech industries based on SWARA-COPRAS approach. Technological and Economic Development of Economy, 20(3), 534–553.