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AHP Ağırlıklı Gri İlişkisel Analiz Kullanarak BIST Bilişim ve Teknoloji Endeksinde (XUTEK) Finansal Oranlar Analizi

Year 2021, Volume 9, Issue 6, 195 - 209, 31.12.2021
https://doi.org/10.29130/dubited.1011252

Abstract

Finansal oran analizi, birçok alt sektör endeksine sahip borsalar için önemli bir konudur. Endüstri 4.0 devrimi ve geçiş sürecinde bilgi ve teknoloji sektörü, küresel değişim ve gelişim sürecinde büyük stratejik öneme sahip sektörlerden biri olarak gösterilmektedir. Dolayısıyla bilgi ve teknoloji sektörünün performansı ekonomilere önemli bir katma değer sağlamaktadır. Bu çalışmada, Bilgi ve Teknoloji Sektörü alanında faaliyet gösteren şirketlerin finansal performanslarının değerlendirilmesinde kullanılan uzman görüşleri dikkate alınarak kriterlerin ağırlıklarının belirlenmesinde çok kriterli karar verme (ÇKKV) yaklaşımları kullanılacaktır. ÇKKV yöntemleri ile şirketlerin finansal performanslarını ölçmek için finansal tablolardan elde edilen likidite, operasyonel/faaliyet, finansal yapı ve karlılık oranları bilimsel literatürde sıklıkla uygulanmaktadır. Çalışmada, analitik hiyerarşi süreç yönteminin ikili karşılaştırma özelliği ile uzman görüşleri kullanılarak kriter ağırlıkları tespit edilmiştir. Daha sonra, 2020 yılında üçer aylık dönemlerdeki finansal oran değerlerinin en küçük ve en büyük değerleri ile oluşan belirsizlik gri ilişkisel analiz yöntemi ile değerlendirilmiştir. Sonuçta; finansal performans açısından öncelikli yatırım portföyüne alınacak XUTEK hisse senetleri belirlenmiştir

References

  • [1] M. Tekin and M. Zerenler, İş Dünyası İçin Krizi Yönetebilmenin Sırları. Konya, Türkiye: Çizgi Kitabevi, 2005.
  • [2] F. A. N. Tayyar, E. Genç and I. Erem, “BİST’e Kayıtlı Bilişim ve Teknoloji alanında Faaliyet Gösteren İşletmelerin Finansal Performanslarının Analitik Hiyerarşi Prosesi (AHP) ve Gri İlişkisel Analiz (GİA) yöntemiyle değerlendirilmesi,” Muhasebe ve Finansman Dergisi, c. 2014, s. 61, ss. 19-40, 2014.
  • [3] I. Aydın, “Bilişim sektörü ve Türkiye’nin sektördeki potansiyeli,” International Journal of New Trends in Arts, Sports & Science Education, vol. 1, no. 1, pp. 180-200, 2012.
  • [4] C. Ceylan and U. Çağlar, Küreselleşmenin Sektörel Etkileri: Araştırma Projesi. İstanbul, Türkiye: İstanbul Ticaret Odası Yayınları Küresel Ekonomik Araştırmalar, 2011.
  • [5] I. Marković, M., Stojanović, J., Stanković, and M. Stanković, “Stock market trend prediction using AHP and weighted kernel LS-SVM,” Soft Computing, vol. 21, no. 18, pp. 5387-5398, 2017.
  • [6] S. Lin and S. Ling-Wu, “Is grey relational analysis superior to the conventional techniques in predicting financial crisis?,” Expert Systems with Applications, vol. 38, no. 5, pp. 5119-5124, 2011.
  • [7] A. Ozdemir and M. Deste, “Gri ilişkisel analiz ile çok kriterli tedarikçi seçimi: otomotiv sektöründe bir uygulama,” İstanbul Üniversitesi İşletme Fakültesi Dergisi, c. 38, s. 2, ss. 147-156, 2009.
  • [8] I. Peker and B. Baki, “Performance Evaluation in Turkish Insurance Sector with Grey Relationship Analysis,” International Journal of Economic and Administrative Studies, vol. 3, no. 7, pp. 1-17, 2011.
  • [9] C. Wu, C. T. Ru-Lin and P. H. Tsai, “Evaluating business performance of wealth management banks,” European Journal of Operational Research, vol. 207, no. 2, pp. 971-979, 2010.
  • [10] Y. Sahin and H. Akyer, “Efficient use of country resources: practice of the AHP and topsis methods in selection of 4x4 search and Rescue (Sar) vehicle,” Süleyman Demirel University Visionary Journal, vol. 3, no. 5, pp. 72-87, 2011.
  • [11] T. Poklepović and Z. Babić, “Stock selection using a hybrid MCDM approach,” Croatian Operational Research Review, vol. 5, no. 2, pp. 273-290, 2014.
  • [12] C. T. Tsao, “A fuzzy MCDM approach for stock selection,” Journal of the Operational Research Society, vol. 57, no. 11, pp. 1341-1352, 2006.
  • [13] H. S. A. V. K. Hota and S. K. Singhai, “Comparative analysis of AHP and its integrated techniques applied for stock index ranking,” in Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, P. K. Sa, M. N. Sahoo, M. Murugappan, Y. Wu, B. Majhi Eds., Singapore, Springer, 2018, pp. 127-134.
  • [14] M. M. M. H. A. M. A. Momeni, J. S. Moradi and J. Mohammadi, “A fuzzy MCDM approach for evaluating listed private banks in Tehran stock exchange based on balanced scorecard,” International Journal of Business Administration, vol. 2, no. 1, pp. 80-97, 2011.
  • [15] E. F. E. A. Mills, M. A. Baafi, N. Amowine and K. Zeng, “A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange,” Journal of Business Economics and Management, vol. 21, no. 2, pp. 446-472, 2020.
  • [16] W. R. J. Ho, C. L. Tsai, G. H. Tzeng and S. K. Fang, “Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM,” Expert Systems with Applications, vol. 38, no. 1, pp. 16-25, 2011.
  • [17] R. Dash, S. Samal, R. Dash and R. Rautray, “An integrated TOPSIS crow search based classifier ensemble: In application to stock index price movement prediction,” Applied Soft Computing, vol. 85, no. 105784, 2019.
  • [18] G. P. Y. Kou and G. Wang, “Evaluation of clustering algorithms for financial risk analysis using MCDM methods,” Information Sciences, vol. 275, pp. 1-12, 2014.
  • [19] P. J. G. Pineda, J. J. Liou, C. C. Hsu and Y. C. Chuang, “An integrated MCDM model for improving airline operational and financial performance,” Journal of Air Transport Management, vol. 68, pp. 103-117, 2018.
  • [20] A. Safaei Ghadikolaei, S. Khalili Esbouei and J. Antucheviciene, “Applying fuzzy MCDM for financial performance evaluation of Iranian companies,” Technological and Economic Development of Economy, vol. 20, no. 2, pp. 274-291, 2014.
  • [21] W. S. Lee, G. H. Tzeng, J. L. Guan, K. T. Chien and J. M. Huang, “Combined MCDM techniques for exploring stock selection based on Gordon model,” Expert Systems with Applications, vol. 36, no. 3, pp. 6421-6430, 2009.
  • [22] H. Bagci and C. Y. Kaygin, “The Financial Performance Measurement of the Companies Listed In The BIST Holding and Investment Index by the MCDM Methods,” The Journal of Accounting and Finance, vol. 87, pp. 301-324, 2020.
  • [23] M. Baydas and O. E. Elma, “An objectıve 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, vol. 4, no. 2, pp. 257-279, 2021.
  • [24] E. Aldalou and S. Perçin, “Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector,” International Journal of Procurement Management, vol. 13, no. 1, pp. 1-23, 2020.
  • [25] K. H. Chen and T. A. Shimerda, “An empirical analysis of useful financial ratios,” Financial management, vol. 10, no. 1 pp. 51-60, 1981.
  • [26] P. Barnes, “The analysis and use of financial ratios,” Journal of Business Finance dan Accounting, vol. 14, no. 4, pp. 449-461, 1987.
  • [27] J. Lewellen, “Predicting returns with financial ratios,” Journal of Financial Economics, vol. 74, no. 2, pp. 209-235, 2004.
  • [28] H. Ozturk and T. A. Karabulut, “The relationship between earnings-to-price, current ratio, profit margin and return: an empirical analysis on Istanbul stock exchange,” Accounting and Finance Research, vol. 7, no. 1, pp. 109-115, 2018.
  • [29] H. O. Sarıdogan, “Financial Performance Analysis of Firms Which are Quated in Tehnology Index in the BIST,” CAKU Journal of Institute of Social Sciences, vol. 11, no. 2, pp. 22-36, 2020.
  • [30] A. S. Temur, “The Effect of Covıd-19 Outbreak on BIST Technology Index (XUTEK),” International Review of Economics and Management, vol. 9, no. 1, pp. 28-49, 2021.
  • [31] F. Zahedi, “The analytic hierarchy process—a survey of the method and its applications,” Interfaces, vol. 16, no. 4, pp. 96-108, 1986.
  • [32] T. Saaty, “How to make a decision: the analytic hierarchy process,” Interfaces, vol. 24, no. 6, pp. 19-43, 1994.
  • [33] T. Saaty. The Analytic Hierarchy Process, New York, USA: McGraw-Hill, 1980.
  • [34] M. Dagdeviren and T. Eren, “Analytical Hierarchy Process and Use of 0-1 Goal Programming Methods in Selecting Supplier Firm,” J. Fac. Eng. Arch. Gazi Univ, vol. 16, no. 2, pp. 41-52, 2001.
  • [35] C. Kahraman, U. Cebeci and Z. and Ulukan, “Multi‐criteria supplier selection using fuzzy AHP,” Logistics Information Management, vol. 16, no. 6, pp. 382-394, 2003.
  • [36] F. T. Chan, N. Kumar, M. K. Tiwari, H. C. Lau and K. Choy, “Global supplier selection: a fuzzy-AHP approach,” International Journal of Production Research, vol. 46, no. 14, pp. 3825-3857, 2008.
  • [37] F. Dweiri, S. Kumar, S. A. Khan and V. Jain, “Designing an integrated AHP based decision support system for supplier selection in automotive industry,” Expert Systems with Applications, vol. 62, pp. 273-283, 2016.
  • [38] S. H. Zyoud and D. Fuchs-Hanusch, “A bibliometric-based survey on AHP and TOPSIS techniques,” Expert Systems with Applications, vol. 78, pp. 158-181, 2017.
  • [39] C.-M. Feng and R.-T. Wang, “Performance evaluation for airlines including the consideration of financial ratios,” Journal of Air Transport Management, vol. 6, no. 3, pp. 133-142, 2000.
  • [40] S. Liu, Y. Yang, Y. Cao and N. Xie, “A summary on the research of GRA models,” Grey Systems: Theory and Application, vol. 3, no. 1, pp. 7-15, 2013.
  • [41] G. Wei, “Grey relational analysis method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information,” Expert Systems with Applications, vol. 38, no. 5, pp. 4824-4828, 2011.
  • [42] E. Aydemir and Y. Sahin, “Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center,” Grey Systems: Theory and Application, vol. 9, no. 4, pp. 432-448, 2019.
  • [43] Y. Sahin and E. Aydemir, “An AHP-weighted grey relational analysis method to determine the technical characteristics’ importance levels of the smartphone,” Eskişehir Osmangazi University Journal of Economics and Administrative Sciences, vol. 14, no. 1, pp. 225-238, 2019.
  • [44] H. Wu, “A comparative study of using grey relational analysis in multiple attribute decision making problems,” Quality Engineering, vol. 159, no. 2, pp. 209-217, 2002.
  • [45] T. Sarı, K. Baynal and O. Ergul, “Supplier selection with grey relational analysis,” International Journal of Emerging Research in Management & Technology, vol. 5, pp. 61-70, 2016.
  • [46] E. Aydemir, F. Bedir and G. Ozdemir, “Degree of greyness approach for an EPQ model with imperfect items in copper wire industry,” Journal of Grey System, vol. 27, no. 2, pp. 13-26, 2015.

A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis

Year 2021, Volume 9, Issue 6, 195 - 209, 31.12.2021
https://doi.org/10.29130/dubited.1011252

Abstract

The financial ratio analysis is an important issue for the stock exchange markets which have many sub-sectoral indexes. During Industry 4.0 revolution and transition, the sector of information and technology is shown as one of the sectors that have great strategic importance in the global change and development process. So, the performance of the information and technology sector provides a significant added value to the economies. In this study, multi-criteria decision-making (MCDM) approaches will be used to determine the weights of the criteria with considering the experts’ opinions used in the evaluation of the financial performance of the companies operating in the field of Information and Technology Sector of BIST Stock Index (XUTEK). In order to measure the financial performance of companies with MCDM methods, the ratios of the liquidity, operational/activity, financial structure, and profitability are obtained from the financial statements are frequently applied in the scientific literature. In the study, criteria weights were determined by using the pairwise comparison feature of the analytical hierarchy process method and expert opinions. Then, the smallest and largest values of the financial ratio values in quarterly periods in 2020 and the uncertainty formed were evaluated with the gray relational analysis method. After all; XUTEK stocks to be included in the priority investment portfolio in terms of financial performance have been determined.

References

  • [1] M. Tekin and M. Zerenler, İş Dünyası İçin Krizi Yönetebilmenin Sırları. Konya, Türkiye: Çizgi Kitabevi, 2005.
  • [2] F. A. N. Tayyar, E. Genç and I. Erem, “BİST’e Kayıtlı Bilişim ve Teknoloji alanında Faaliyet Gösteren İşletmelerin Finansal Performanslarının Analitik Hiyerarşi Prosesi (AHP) ve Gri İlişkisel Analiz (GİA) yöntemiyle değerlendirilmesi,” Muhasebe ve Finansman Dergisi, c. 2014, s. 61, ss. 19-40, 2014.
  • [3] I. Aydın, “Bilişim sektörü ve Türkiye’nin sektördeki potansiyeli,” International Journal of New Trends in Arts, Sports & Science Education, vol. 1, no. 1, pp. 180-200, 2012.
  • [4] C. Ceylan and U. Çağlar, Küreselleşmenin Sektörel Etkileri: Araştırma Projesi. İstanbul, Türkiye: İstanbul Ticaret Odası Yayınları Küresel Ekonomik Araştırmalar, 2011.
  • [5] I. Marković, M., Stojanović, J., Stanković, and M. Stanković, “Stock market trend prediction using AHP and weighted kernel LS-SVM,” Soft Computing, vol. 21, no. 18, pp. 5387-5398, 2017.
  • [6] S. Lin and S. Ling-Wu, “Is grey relational analysis superior to the conventional techniques in predicting financial crisis?,” Expert Systems with Applications, vol. 38, no. 5, pp. 5119-5124, 2011.
  • [7] A. Ozdemir and M. Deste, “Gri ilişkisel analiz ile çok kriterli tedarikçi seçimi: otomotiv sektöründe bir uygulama,” İstanbul Üniversitesi İşletme Fakültesi Dergisi, c. 38, s. 2, ss. 147-156, 2009.
  • [8] I. Peker and B. Baki, “Performance Evaluation in Turkish Insurance Sector with Grey Relationship Analysis,” International Journal of Economic and Administrative Studies, vol. 3, no. 7, pp. 1-17, 2011.
  • [9] C. Wu, C. T. Ru-Lin and P. H. Tsai, “Evaluating business performance of wealth management banks,” European Journal of Operational Research, vol. 207, no. 2, pp. 971-979, 2010.
  • [10] Y. Sahin and H. Akyer, “Efficient use of country resources: practice of the AHP and topsis methods in selection of 4x4 search and Rescue (Sar) vehicle,” Süleyman Demirel University Visionary Journal, vol. 3, no. 5, pp. 72-87, 2011.
  • [11] T. Poklepović and Z. Babić, “Stock selection using a hybrid MCDM approach,” Croatian Operational Research Review, vol. 5, no. 2, pp. 273-290, 2014.
  • [12] C. T. Tsao, “A fuzzy MCDM approach for stock selection,” Journal of the Operational Research Society, vol. 57, no. 11, pp. 1341-1352, 2006.
  • [13] H. S. A. V. K. Hota and S. K. Singhai, “Comparative analysis of AHP and its integrated techniques applied for stock index ranking,” in Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, P. K. Sa, M. N. Sahoo, M. Murugappan, Y. Wu, B. Majhi Eds., Singapore, Springer, 2018, pp. 127-134.
  • [14] M. M. M. H. A. M. A. Momeni, J. S. Moradi and J. Mohammadi, “A fuzzy MCDM approach for evaluating listed private banks in Tehran stock exchange based on balanced scorecard,” International Journal of Business Administration, vol. 2, no. 1, pp. 80-97, 2011.
  • [15] E. F. E. A. Mills, M. A. Baafi, N. Amowine and K. Zeng, “A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange,” Journal of Business Economics and Management, vol. 21, no. 2, pp. 446-472, 2020.
  • [16] W. R. J. Ho, C. L. Tsai, G. H. Tzeng and S. K. Fang, “Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM,” Expert Systems with Applications, vol. 38, no. 1, pp. 16-25, 2011.
  • [17] R. Dash, S. Samal, R. Dash and R. Rautray, “An integrated TOPSIS crow search based classifier ensemble: In application to stock index price movement prediction,” Applied Soft Computing, vol. 85, no. 105784, 2019.
  • [18] G. P. Y. Kou and G. Wang, “Evaluation of clustering algorithms for financial risk analysis using MCDM methods,” Information Sciences, vol. 275, pp. 1-12, 2014.
  • [19] P. J. G. Pineda, J. J. Liou, C. C. Hsu and Y. C. Chuang, “An integrated MCDM model for improving airline operational and financial performance,” Journal of Air Transport Management, vol. 68, pp. 103-117, 2018.
  • [20] A. Safaei Ghadikolaei, S. Khalili Esbouei and J. Antucheviciene, “Applying fuzzy MCDM for financial performance evaluation of Iranian companies,” Technological and Economic Development of Economy, vol. 20, no. 2, pp. 274-291, 2014.
  • [21] W. S. Lee, G. H. Tzeng, J. L. Guan, K. T. Chien and J. M. Huang, “Combined MCDM techniques for exploring stock selection based on Gordon model,” Expert Systems with Applications, vol. 36, no. 3, pp. 6421-6430, 2009.
  • [22] H. Bagci and C. Y. Kaygin, “The Financial Performance Measurement of the Companies Listed In The BIST Holding and Investment Index by the MCDM Methods,” The Journal of Accounting and Finance, vol. 87, pp. 301-324, 2020.
  • [23] M. Baydas and O. E. Elma, “An objectıve 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, vol. 4, no. 2, pp. 257-279, 2021.
  • [24] E. Aldalou and S. Perçin, “Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector,” International Journal of Procurement Management, vol. 13, no. 1, pp. 1-23, 2020.
  • [25] K. H. Chen and T. A. Shimerda, “An empirical analysis of useful financial ratios,” Financial management, vol. 10, no. 1 pp. 51-60, 1981.
  • [26] P. Barnes, “The analysis and use of financial ratios,” Journal of Business Finance dan Accounting, vol. 14, no. 4, pp. 449-461, 1987.
  • [27] J. Lewellen, “Predicting returns with financial ratios,” Journal of Financial Economics, vol. 74, no. 2, pp. 209-235, 2004.
  • [28] H. Ozturk and T. A. Karabulut, “The relationship between earnings-to-price, current ratio, profit margin and return: an empirical analysis on Istanbul stock exchange,” Accounting and Finance Research, vol. 7, no. 1, pp. 109-115, 2018.
  • [29] H. O. Sarıdogan, “Financial Performance Analysis of Firms Which are Quated in Tehnology Index in the BIST,” CAKU Journal of Institute of Social Sciences, vol. 11, no. 2, pp. 22-36, 2020.
  • [30] A. S. Temur, “The Effect of Covıd-19 Outbreak on BIST Technology Index (XUTEK),” International Review of Economics and Management, vol. 9, no. 1, pp. 28-49, 2021.
  • [31] F. Zahedi, “The analytic hierarchy process—a survey of the method and its applications,” Interfaces, vol. 16, no. 4, pp. 96-108, 1986.
  • [32] T. Saaty, “How to make a decision: the analytic hierarchy process,” Interfaces, vol. 24, no. 6, pp. 19-43, 1994.
  • [33] T. Saaty. The Analytic Hierarchy Process, New York, USA: McGraw-Hill, 1980.
  • [34] M. Dagdeviren and T. Eren, “Analytical Hierarchy Process and Use of 0-1 Goal Programming Methods in Selecting Supplier Firm,” J. Fac. Eng. Arch. Gazi Univ, vol. 16, no. 2, pp. 41-52, 2001.
  • [35] C. Kahraman, U. Cebeci and Z. and Ulukan, “Multi‐criteria supplier selection using fuzzy AHP,” Logistics Information Management, vol. 16, no. 6, pp. 382-394, 2003.
  • [36] F. T. Chan, N. Kumar, M. K. Tiwari, H. C. Lau and K. Choy, “Global supplier selection: a fuzzy-AHP approach,” International Journal of Production Research, vol. 46, no. 14, pp. 3825-3857, 2008.
  • [37] F. Dweiri, S. Kumar, S. A. Khan and V. Jain, “Designing an integrated AHP based decision support system for supplier selection in automotive industry,” Expert Systems with Applications, vol. 62, pp. 273-283, 2016.
  • [38] S. H. Zyoud and D. Fuchs-Hanusch, “A bibliometric-based survey on AHP and TOPSIS techniques,” Expert Systems with Applications, vol. 78, pp. 158-181, 2017.
  • [39] C.-M. Feng and R.-T. Wang, “Performance evaluation for airlines including the consideration of financial ratios,” Journal of Air Transport Management, vol. 6, no. 3, pp. 133-142, 2000.
  • [40] S. Liu, Y. Yang, Y. Cao and N. Xie, “A summary on the research of GRA models,” Grey Systems: Theory and Application, vol. 3, no. 1, pp. 7-15, 2013.
  • [41] G. Wei, “Grey relational analysis method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information,” Expert Systems with Applications, vol. 38, no. 5, pp. 4824-4828, 2011.
  • [42] E. Aydemir and Y. Sahin, “Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center,” Grey Systems: Theory and Application, vol. 9, no. 4, pp. 432-448, 2019.
  • [43] Y. Sahin and E. Aydemir, “An AHP-weighted grey relational analysis method to determine the technical characteristics’ importance levels of the smartphone,” Eskişehir Osmangazi University Journal of Economics and Administrative Sciences, vol. 14, no. 1, pp. 225-238, 2019.
  • [44] H. Wu, “A comparative study of using grey relational analysis in multiple attribute decision making problems,” Quality Engineering, vol. 159, no. 2, pp. 209-217, 2002.
  • [45] T. Sarı, K. Baynal and O. Ergul, “Supplier selection with grey relational analysis,” International Journal of Emerging Research in Management & Technology, vol. 5, pp. 61-70, 2016.
  • [46] E. Aydemir, F. Bedir and G. Ozdemir, “Degree of greyness approach for an EPQ model with imperfect items in copper wire industry,” Journal of Grey System, vol. 27, no. 2, pp. 13-26, 2015.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Tunahan TURHAN> (Primary Author)
SÜLEYMAN DEMİREL ÜNİVERSİTESİ
0000-0002-9632-2180
Palestine, State of


Erdal AYDEMİR>
SÜLEYMAN DEMİREL ÜNİVERSİTESİ
0000-0003-4834-725X
Türkiye

Publication Date December 31, 2021
Published in Issue Year 2021, Volume 9, Issue 6

Cite

Bibtex @research article { dubited1011252, journal = {Düzce Üniversitesi Bilim ve Teknoloji Dergisi}, eissn = {2148-2446}, address = {}, publisher = {Duzce University}, year = {2021}, volume = {9}, number = {6}, pages = {195 - 209}, doi = {10.29130/dubited.1011252}, title = {A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis}, key = {cite}, author = {Turhan, Tunahan and Aydemir, Erdal} }
APA Turhan, T. & Aydemir, E. (2021). A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis . Düzce Üniversitesi Bilim ve Teknoloji Dergisi , ICAIAME 2021 , 195-209 . DOI: 10.29130/dubited.1011252
MLA Turhan, T. , Aydemir, E. "A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis" . Düzce Üniversitesi Bilim ve Teknoloji Dergisi 9 (2021 ): 195-209 <https://dergipark.org.tr/en/pub/dubited/issue/67474/1011252>
Chicago Turhan, T. , Aydemir, E. "A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 9 (2021 ): 195-209
RIS TY - JOUR T1 - A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis AU - TunahanTurhan, ErdalAydemir Y1 - 2021 PY - 2021 N1 - doi: 10.29130/dubited.1011252 DO - 10.29130/dubited.1011252 T2 - Düzce Üniversitesi Bilim ve Teknoloji Dergisi JF - Journal JO - JOR SP - 195 EP - 209 VL - 9 IS - 6 SN - -2148-2446 M3 - doi: 10.29130/dubited.1011252 UR - https://doi.org/10.29130/dubited.1011252 Y2 - 2021 ER -
EndNote %0 Duzce University Journal of Science and Technology A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis %A Tunahan Turhan , Erdal Aydemir %T A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis %D 2021 %J Düzce Üniversitesi Bilim ve Teknoloji Dergisi %P -2148-2446 %V 9 %N 6 %R doi: 10.29130/dubited.1011252 %U 10.29130/dubited.1011252
ISNAD Turhan, Tunahan , Aydemir, Erdal . "A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 9 / 6 (December 2021): 195-209 . https://doi.org/10.29130/dubited.1011252
AMA Turhan T. , Aydemir E. A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis. DUBİTED. 2021; 9(6): 195-209.
Vancouver Turhan T. , Aydemir E. A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis. Düzce Üniversitesi Bilim ve Teknoloji Dergisi. 2021; 9(6): 195-209.
IEEE T. Turhan and E. Aydemir , "A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis", Düzce Üniversitesi Bilim ve Teknoloji Dergisi, vol. 9, no. 6, pp. 195-209, Dec. 2021, doi:10.29130/dubited.1011252