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AHP ve TOPSIS Yöntemleri ile Portföy Seçimi: BİST’de Bir Uygulama

Year 2025, , 181 - 194, 15.04.2025

Şafak Sönmez Soydaş

https://doi.org/10.16951/trendbusecon.1580489

Abstract

Bu çalışmada imalat sanayi sektöründe 2023 yılında faaliyette bulunan şirketlerin verimlilik analizi ve çok kriterli karar verme yöntemleri AHP ve TOPSIS ile düşük-orta-yüksek risk seviyelerinde portföy oluşturmak amaçlanmıştır. Çalışmanın örneklemine Bist imalat sanayi sektöründe faaliyette bulunan ana metal sanayi ve tekstil, giyim eşyası ve deri sanayi firmaları alınmıştır. Bahse konu yılda ana metal sanayinde 28, tekstil, giyim eşyası ve deri sanayinde ise 27 firma bulunmaktadır. Toplam 55 firmadan yeni halka arz olmalarından dolayı 2023 yılı için verilerine ulaşabildiğimiz 48 firma analiz kapsamına alınmıştır. TOPSİS analiz sonuçları, firma kodlarına göre düşük risk grubundaki firmalar (T1, T2, T6, M4, T15, T3), orta risk grubunda ki firmalar (T5, T10, T24, T16, M14, M10) ve yüksek risk grubundaki firmalar (M16, M17, M20, M18, M22, M19) sıralanmıştır. Risk grubu ölçütlerine göre ise, yüksek risk grubunda ki firma (T15), Orta risk grubundaki firmalar (T1, T2, T3, T5, T6, T10, T24) ve düşük risk grubu firmaları ise (T16, M4, M10, M14, M16, M17, M18, M19, M20, M22) sıralanmıştır. Spearman korelasyon analizi sonuçlarına göre, TOPSIS skorları ile risk grupları arasında pozitif bir ilişki gözlemlenmiştir (r = 0.412), ancak bu ilişki istatistiksel olarak anlamlı değildir (p = 0.090).

Keywords

Finansal Oranlar AHP TOPSIS

References

  • Aktaş, R., & Ulusoy, A. (2014). Performance evaluation of manufacturing firms listed in Borsa Istanbul by using TOPSIS. Journal of the Faculty of Economics and Administrative Sciences, 29(2), 175-191.
  • Ayçin, E., & Çakın, E. (2019). KOBİ’lerin Finansal Performansının MACBETH-COPRAS Bütünleşik Yaklaşımıyla Değerlendirilmesi. Yaşar Üniversitesi E-Dergisi, 14(55), 251-265. [CrossRef]
  • Azadeh, A., Ghaderi, S. F., & Rajabzadeh, A. (2011). Integration of DEA and AHP with computer simulation for railway system performance assessment and improvement. Applied Mathematics and Computation, 217(24), 10282-10290. [CrossRef]
  • Bal, H. M., & Örkcü, H. H. (2021). Veri zarflama analizi ve TOPSIS yöntemleri ile optimal hisse senedi seçimi: Borsa İstanbul üzerine bir uygulama. Journal of Yasar University, 16(63), 181-193. [CrossRef]
  • Beccali, M., Cellura, M., & Ardente, F. (2004). Decision making in energy planning: The use of multi-criteria decision analysis and data envelopment analysis. Energy, 29(10), 1225-1244. [CrossRef]
  • Benitez, J. M., Martín, J. C., & Román, C. (2007). Using fuzzy number for measuring quality of service in the hotel industry. Tourism Management, 28(2), 544-555. [CrossRef]
  • Chaweewanchon, A., & Chaysiri, R. (2022). Markowitz mean-variance portfolio optimization with predictive stock selection using machine learning. Expert Systems with Applications, 188, 114190. [CrossRef]
  • Charnes, A., Cooper, W. W., & Li, S. (1989). Using data envelopment analysis to evaluate efficiency in the economic performance of Chinese cities. Socio-Economic Planning Sciences, 23(6), 325-344. [CrossRef]
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. [CrossRef]
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1981). Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through. Management Science, 27. [CrossRef]
  • Corporate Finance Institute (CFI). (2023). What is Beta in Finance? CFI. https://corporatefinanceinstitute.com in 09.17.2024.
  • Çetin, B., & Yıldırım, S. (2018). BIST tekstil ve metal sektörlerinde finansal performans değerlendirmesi: Çok kriterli karar verme yöntemleriyle bir inceleme. İşletme ve Ekonomi Araştırmaları Dergisi, 9(3), 45-65. [CrossRef]
  • Dervişoğlu, M., & Kurt, B. (2017). Veri zarflama analizi ve TOPSIS yöntemi ile hisse senedi performanslarının karşılaştırılması: BİST bankacılık endeksi üzerine bir uygulama. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 8(19), 51-62. [CrossRef]
  • Doğan, M. (2016). Finansal performans analizinde TOPSIS yöntemi: BİST’te işlem gören metal ve tekstil sektörü firmaları üzerine bir araştırma. Finansal Araştırmalar ve Çalışmalar Dergisi, 8(15), 1-20. [CrossRef]
  • Eurometal (ECSC). (2022). Turkey Data: Steel exports up 20% to record 19.9 million mt in 2021: TCUD. EUROMETAL. https://eurometal.net/turkey-data-steel-exports-up-20-to-record-19-9-million-mt-in-2021-tcud in 09.15.2024.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-290. [CrossRef]
  • Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple criteria decision analysis: State of the art surveys. Springer Science and Business Media. [CrossRef]
  • Ghaffari, M., Mahdavi-Amiri, N., & Zarei, H. (2021). Robust portfolio selection problems: A comprehensive review. Omega, 100, 102225. [CrossRef]
  • Güngör, G., & Gözgör, G. (2015). A combined DEA and multi-criteria decision making approach for mutual fund selection. Journal of Applied Finance and Banking, 5(2), 19-32.
  • Ho, W. (2008). Integrated analytic hierarchy process and its applications – A literature review. European Journal of Operational Research, 186(1), 211-228. [CrossRef]
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer. [CrossRef]
  • Investopedia. (2023). What beta means when considering a stock's risk. Investopedia. https://www.investopedia.com in 09.17.2024.
  • Investopedia. (2023). What is a good debt-to-equity ratio and why it matters. Investopedia. https://www.investopedia.com/terms/d/debtequityratio.asp in 09.17.2024.
  • Investing Answers. (2023). Debt-to-Equity (D/E) Ratio. Investing Answers. https://www.investinganswers.com/dictionary/d/debt-equity-ratio in 09.17.2024.
  • Investing. (2023). Debt to Equity Ratio Explained. https://www.investing.com in 09.17.2024.
  • Jing, D., Imeni, M., Edalatpanah, S. A., Alburaikan, A., & Khalifa, H. A. E. W. (2023). Optimal selection of stock portfolios using multi-criteria decision-making methods. Mathematics, 11(2), 415. [CrossRef]
  • Kucukaltan, B., & Aydin, G. (2015). An integrated AHP-TOPSIS model for performance evaluation of airport traffic controllers. Journal of Air Transport Management, 42, 101-109. [CrossRef]
  • Küçük, C., & Büyükbaş, S. (2017). Sektörel performans analizinde TOPSIS ve VIKOR yöntemlerinin karşılaştırılması. Journal of Business Research-Türk, 9(2), 125-138. [CrossRef]
  • Lozano, S., & Gutiérrez, E. (2008). DEA and simulation for measuring efficiency in port terminals. Annals of Operations Research, 153(1), 21-43. [CrossRef]
  • Lozano, S., & Villa, G. (2006). Data envelopment analysis of mutual funds based on second-order stochastic dominance. European Journal of Operational Research, 172(1), 295-309. [CrossRef]
  • Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91. [CrossRef]
  • Meade, N., & Islam, T. (2015). Modelling and forecasting the performance of stock indices using neural networks and TOPSIS. Expert Systems with Applications, 42(4), 1979-1990. [CrossRef]
  • Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. American Economic Review, 48(3), 261-297. [CrossRef]
  • Oliveira, M. S., Steffen, V., Francisco, A. C., & Trojan, F. (2023). Integrated data envelopment analysis, multi-criteria decision making, and cluster analysis methods: Trends and perspectives. Decision Analytics Journal, 8, 100271.
  • Peykani, P., Mohammadi, E., Jabbarzadeh, A., Rostamy-Malkhalifeh, M., & Pishvaee, M. S. (2020). A novel two-phase robust portfolio selection and optimization approach under uncertainty: A case study of Tehran stock exchange. Plos One, 15(10), e0239810. https://doi.org/10.1371/journal.pone.0239810.
  • Roodposhti, F. R., Jahromi, M. B., & Kamalzadeh, S. (2018). Portfolio selection using analytic hierarchy process and numerical taxonomy analysis: Case study of Iran. Am. J. Financ. Account, 5, 394. [CrossRef]
  • Saaty, T. L. (1980). The analytic hierarchy process (AHP). The Journal of the Operational Research Society, 41(11), 1073-1076. [CrossRef]
  • Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using Analytic Hierarchy Process and TOPSIS. Expert Systems with Applications, 36(9), 11699-11709. [CrossRef]
  • Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425-442. [CrossRef]
  • Smętek, K., Zawadzka, D., & Strzelecka, A. (2022). Examples of the use of data envelopment analysis (DEA) to assess the financial effectiveness of insurance companies. Procedia Computer Science, 207, 3924-3930. [CrossRef]
  • Thakur, G. S. M., Bhattacharyya, R., & Sarkar, S. (2018). Stock portfolio selection using Dempster–Shafer evidence theory. Journal of King Saud University-Computer and Information Sciences, 30(2), 223-235. [CrossRef]
  • Thanassoulis, E., Portela, M. C., & Despic, O. (2008). Data envelopment analysis: the mathematical programming approach to efficiency analysis. The Measurement Of Productive Efficiency And Productivity Growth, 251-420. [CrossRef]
  • The Observatory of Economic Complexity (OEC). (2022). Iron and steel in Turkey. OEC. https://oec.world/en/profile/bilateral-product/ironsteel/reporter/tur in 09.15.2024.
  • Turkish Goods. (2021). Exports skyrocket in the Turkish textile sector. Turkish Goods. https://www.turkishgoods.com in 15.09.2024.
  • Wei, C., & Zhang, W. (2020). Performance evaluation and portfolio selection using data envelopment analysis and Markowitz model: Evidence from the Chinese stock market. Journal of Computational and Applied Mathematics, 380, 112967. [CrossRef]
  • Yalcin, N., & Unlu, U. (2018). Financial performance measurement of Turkish real estate investment trusts using TOPSIS. Journal of Yasar University, 13(50), 2501-2511.
  • Yüksel, S., & Canöz, İ. (2015). BIST metal ve tekstil sektörlerinde finansal performansın TOPSIS yöntemiyle değerlendirilmesi. Muhasebe ve Finansman Dergisi, 67, 89-104.
  • Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). Multi-criteria decision-making (MCDM) methods in economics: An overview of weighted methods. Technological and Economic Development of Economy, 20(2), 326-342. [CrossRef]
  • Zolfani, S. H., Chen, I. S., Rezaeiniya, N., & Tamošaitienė, J. (2012). A hybrid MCDM model encompassing AHP and COPRAS-G methods for selecting company supplier in Iran. Technological and Economic Development of Economy, 18(3), 529-543. [CrossRef]
  • Zopounidis, C., & Doumpos, M. (2013). Intelligent decision aiding systems based on multiple criteria for financial engineering (Vol. 38). Springer Science & Business Media.

Portfolio Selection with AHP and TOPSIS Methods: An Application in BIST

Year 2025, , 181 - 194, 15.04.2025

Şafak Sönmez Soydaş

https://doi.org/10.16951/trendbusecon.1580489

Abstract

In this study, the intend is to create portfolios at low, medium, and high-risk levels for firms operating in the fabrication sector in 2023 by utilizing efficiency analysis and multi-criteria decision-making methods, AHP and TOPSIS. The sample of the study comprises companies from the basic metal and textile, apparel, and leather industries listed in the BIST manufacturing sector. In the mentioned year, there were 28 firms in the basic metal industry and 27 firms in the textile, apparel, and leather industries. From the overall of 55 companies, data from 48 firms were available for the year 2023 due to recent initial public offerings, and these were included in the analysis. According to TOPSIS analysis results, companies in the low-risk group, based on firm codes, are (T1, T2, T6, M4, T15, T3), medium-risk group companies are (T5, T10, T24, T16, M14, M10), and high-risk group companies are (M16, M17, M20, M18, M22, M19). Based on risk group criteria, firms in the high-risk group include (T15), companies in the medium-risk group are (T1, T2, T3, T5, T6, T10, T24), and firms in the low-risk group are (T16, M4, M10, M14, M16, M17, M18, M19, M20, M22). As indicated by aftermath of the Spearman correlation analysis, a positive correlation was observed amid the TOPSIS scores and the risk groups (r = 0.412); however, this connection is not statistically important (p = 0.090).

Keywords

Financial Rasio AHP TOPSIS

References

  • Aktaş, R., & Ulusoy, A. (2014). Performance evaluation of manufacturing firms listed in Borsa Istanbul by using TOPSIS. Journal of the Faculty of Economics and Administrative Sciences, 29(2), 175-191.
  • Ayçin, E., & Çakın, E. (2019). KOBİ’lerin Finansal Performansının MACBETH-COPRAS Bütünleşik Yaklaşımıyla Değerlendirilmesi. Yaşar Üniversitesi E-Dergisi, 14(55), 251-265. [CrossRef]
  • Azadeh, A., Ghaderi, S. F., & Rajabzadeh, A. (2011). Integration of DEA and AHP with computer simulation for railway system performance assessment and improvement. Applied Mathematics and Computation, 217(24), 10282-10290. [CrossRef]
  • Bal, H. M., & Örkcü, H. H. (2021). Veri zarflama analizi ve TOPSIS yöntemleri ile optimal hisse senedi seçimi: Borsa İstanbul üzerine bir uygulama. Journal of Yasar University, 16(63), 181-193. [CrossRef]
  • Beccali, M., Cellura, M., & Ardente, F. (2004). Decision making in energy planning: The use of multi-criteria decision analysis and data envelopment analysis. Energy, 29(10), 1225-1244. [CrossRef]
  • Benitez, J. M., Martín, J. C., & Román, C. (2007). Using fuzzy number for measuring quality of service in the hotel industry. Tourism Management, 28(2), 544-555. [CrossRef]
  • Chaweewanchon, A., & Chaysiri, R. (2022). Markowitz mean-variance portfolio optimization with predictive stock selection using machine learning. Expert Systems with Applications, 188, 114190. [CrossRef]
  • Charnes, A., Cooper, W. W., & Li, S. (1989). Using data envelopment analysis to evaluate efficiency in the economic performance of Chinese cities. Socio-Economic Planning Sciences, 23(6), 325-344. [CrossRef]
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. [CrossRef]
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1981). Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through. Management Science, 27. [CrossRef]
  • Corporate Finance Institute (CFI). (2023). What is Beta in Finance? CFI. https://corporatefinanceinstitute.com in 09.17.2024.
  • Çetin, B., & Yıldırım, S. (2018). BIST tekstil ve metal sektörlerinde finansal performans değerlendirmesi: Çok kriterli karar verme yöntemleriyle bir inceleme. İşletme ve Ekonomi Araştırmaları Dergisi, 9(3), 45-65. [CrossRef]
  • Dervişoğlu, M., & Kurt, B. (2017). Veri zarflama analizi ve TOPSIS yöntemi ile hisse senedi performanslarının karşılaştırılması: BİST bankacılık endeksi üzerine bir uygulama. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 8(19), 51-62. [CrossRef]
  • Doğan, M. (2016). Finansal performans analizinde TOPSIS yöntemi: BİST’te işlem gören metal ve tekstil sektörü firmaları üzerine bir araştırma. Finansal Araştırmalar ve Çalışmalar Dergisi, 8(15), 1-20. [CrossRef]
  • Eurometal (ECSC). (2022). Turkey Data: Steel exports up 20% to record 19.9 million mt in 2021: TCUD. EUROMETAL. https://eurometal.net/turkey-data-steel-exports-up-20-to-record-19-9-million-mt-in-2021-tcud in 09.15.2024.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-290. [CrossRef]
  • Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple criteria decision analysis: State of the art surveys. Springer Science and Business Media. [CrossRef]
  • Ghaffari, M., Mahdavi-Amiri, N., & Zarei, H. (2021). Robust portfolio selection problems: A comprehensive review. Omega, 100, 102225. [CrossRef]
  • Güngör, G., & Gözgör, G. (2015). A combined DEA and multi-criteria decision making approach for mutual fund selection. Journal of Applied Finance and Banking, 5(2), 19-32.
  • Ho, W. (2008). Integrated analytic hierarchy process and its applications – A literature review. European Journal of Operational Research, 186(1), 211-228. [CrossRef]
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer. [CrossRef]
  • Investopedia. (2023). What beta means when considering a stock's risk. Investopedia. https://www.investopedia.com in 09.17.2024.
  • Investopedia. (2023). What is a good debt-to-equity ratio and why it matters. Investopedia. https://www.investopedia.com/terms/d/debtequityratio.asp in 09.17.2024.
  • Investing Answers. (2023). Debt-to-Equity (D/E) Ratio. Investing Answers. https://www.investinganswers.com/dictionary/d/debt-equity-ratio in 09.17.2024.
  • Investing. (2023). Debt to Equity Ratio Explained. https://www.investing.com in 09.17.2024.
  • Jing, D., Imeni, M., Edalatpanah, S. A., Alburaikan, A., & Khalifa, H. A. E. W. (2023). Optimal selection of stock portfolios using multi-criteria decision-making methods. Mathematics, 11(2), 415. [CrossRef]
  • Kucukaltan, B., & Aydin, G. (2015). An integrated AHP-TOPSIS model for performance evaluation of airport traffic controllers. Journal of Air Transport Management, 42, 101-109. [CrossRef]
  • Küçük, C., & Büyükbaş, S. (2017). Sektörel performans analizinde TOPSIS ve VIKOR yöntemlerinin karşılaştırılması. Journal of Business Research-Türk, 9(2), 125-138. [CrossRef]
  • Lozano, S., & Gutiérrez, E. (2008). DEA and simulation for measuring efficiency in port terminals. Annals of Operations Research, 153(1), 21-43. [CrossRef]
  • Lozano, S., & Villa, G. (2006). Data envelopment analysis of mutual funds based on second-order stochastic dominance. European Journal of Operational Research, 172(1), 295-309. [CrossRef]
  • Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91. [CrossRef]
  • Meade, N., & Islam, T. (2015). Modelling and forecasting the performance of stock indices using neural networks and TOPSIS. Expert Systems with Applications, 42(4), 1979-1990. [CrossRef]
  • Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. American Economic Review, 48(3), 261-297. [CrossRef]
  • Oliveira, M. S., Steffen, V., Francisco, A. C., & Trojan, F. (2023). Integrated data envelopment analysis, multi-criteria decision making, and cluster analysis methods: Trends and perspectives. Decision Analytics Journal, 8, 100271.
  • Peykani, P., Mohammadi, E., Jabbarzadeh, A., Rostamy-Malkhalifeh, M., & Pishvaee, M. S. (2020). A novel two-phase robust portfolio selection and optimization approach under uncertainty: A case study of Tehran stock exchange. Plos One, 15(10), e0239810. https://doi.org/10.1371/journal.pone.0239810.
  • Roodposhti, F. R., Jahromi, M. B., & Kamalzadeh, S. (2018). Portfolio selection using analytic hierarchy process and numerical taxonomy analysis: Case study of Iran. Am. J. Financ. Account, 5, 394. [CrossRef]
  • Saaty, T. L. (1980). The analytic hierarchy process (AHP). The Journal of the Operational Research Society, 41(11), 1073-1076. [CrossRef]
  • Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using Analytic Hierarchy Process and TOPSIS. Expert Systems with Applications, 36(9), 11699-11709. [CrossRef]
  • Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425-442. [CrossRef]
  • Smętek, K., Zawadzka, D., & Strzelecka, A. (2022). Examples of the use of data envelopment analysis (DEA) to assess the financial effectiveness of insurance companies. Procedia Computer Science, 207, 3924-3930. [CrossRef]
  • Thakur, G. S. M., Bhattacharyya, R., & Sarkar, S. (2018). Stock portfolio selection using Dempster–Shafer evidence theory. Journal of King Saud University-Computer and Information Sciences, 30(2), 223-235. [CrossRef]
  • Thanassoulis, E., Portela, M. C., & Despic, O. (2008). Data envelopment analysis: the mathematical programming approach to efficiency analysis. The Measurement Of Productive Efficiency And Productivity Growth, 251-420. [CrossRef]
  • The Observatory of Economic Complexity (OEC). (2022). Iron and steel in Turkey. OEC. https://oec.world/en/profile/bilateral-product/ironsteel/reporter/tur in 09.15.2024.
  • Turkish Goods. (2021). Exports skyrocket in the Turkish textile sector. Turkish Goods. https://www.turkishgoods.com in 15.09.2024.
  • Wei, C., & Zhang, W. (2020). Performance evaluation and portfolio selection using data envelopment analysis and Markowitz model: Evidence from the Chinese stock market. Journal of Computational and Applied Mathematics, 380, 112967. [CrossRef]
  • Yalcin, N., & Unlu, U. (2018). Financial performance measurement of Turkish real estate investment trusts using TOPSIS. Journal of Yasar University, 13(50), 2501-2511.
  • Yüksel, S., & Canöz, İ. (2015). BIST metal ve tekstil sektörlerinde finansal performansın TOPSIS yöntemiyle değerlendirilmesi. Muhasebe ve Finansman Dergisi, 67, 89-104.
  • Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). Multi-criteria decision-making (MCDM) methods in economics: An overview of weighted methods. Technological and Economic Development of Economy, 20(2), 326-342. [CrossRef]
  • Zolfani, S. H., Chen, I. S., Rezaeiniya, N., & Tamošaitienė, J. (2012). A hybrid MCDM model encompassing AHP and COPRAS-G methods for selecting company supplier in Iran. Technological and Economic Development of Economy, 18(3), 529-543. [CrossRef]
  • Zopounidis, C., & Doumpos, M. (2013). Intelligent decision aiding systems based on multiple criteria for financial engineering (Vol. 38). Springer Science & Business Media.
There are 50 citations in total.

Details

Primary Language English
Subjects Business Administration
Journal Section Research Articles
Authors

Şafak Sönmez Soydaş 0000-0002-7174-8652

Early Pub Date April 14, 2025
Publication Date April 15, 2025
Submission Date November 6, 2024
Acceptance Date March 17, 2025
Published in Issue Year 2025

Cite

APA Soydaş, Ş. S. (2025). Portfolio Selection with AHP and TOPSIS Methods: An Application in BIST. Trends in Business and Economics, 39(2), 181-194. https://doi.org/10.16951/trendbusecon.1580489

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