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A Comparison on Portfolio Selection Problem: Data Envelope Analysis and Mean Variance Methods Example

Yıl 2023, Cilt: 5 Sayı: 2, 122 - 139

Hatice Cenger Erkan Poyraz

Öz

Kaynakça

  • Andersen, P., Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264. https://doi.org/10.1287/mnsc.39.10.1261
  • Basso, A., & Funari, S. (2001). A data envelopment analysis approach to measure the mutual fund performance. European Journal of Operational Research, 135(3), 477-492. https://doi.org/10.1016/S0377-2217(00)00311-8
  • Biswas, S., Bandyopadhyay, G., Guha, B., Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision making framework. Decision Making: Applications in Management and Engineering, 2(2), 138-158.
  • Brown, R., O'Connor, I., Brown, R. (1997). Measurement of efficiency in not-for-profit financial intermediaries: Australian evidence. University of Melbourne, Department of Accounting and Finance.
  • Choi, Y. K., & Murthi, B. P. S. (2001). Relative performance evaluation of mutual funds: A non‐parametric approach. Journal of Business Finance & Accounting, 28(7‐8), 853-876.
  • Charnes, A., Cooper, W. W., and Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., & Rousseau, J. (1984). Sensitivity and stability analysis in DEA. Annals of Operations Research, 2(1), 139-156.
  • Chen, Z., & Lin, R. (2006). Mutual fund performance evaluation using data envelopment analysis with new risk measures. Or Spectrum, 28(3), 375-398.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281. https://doi.org/10.2307/2343100
  • Gregoriou, G. N., Sedzro, K., & Zhu, J. (2005). Hedge fund performance appraisal using data envelopment analysis. European Journal of Operational Research, 164(2), 555-571. https://doi.org/10.1016/j.ejor.2003.12.019
  • Kuosmanen, T. (2007). Performance measurement and best-practice benchmarking of mutual funds: combining stochastic dominance criteria with data envelopment analysis. Journal of Productivity Analysis, 28, 71-86.
  • Liu, J., Ding, F. Y., and Lall, V. (2000). Using data envelopment analysis to compare suppliers for supplier selection and performance improvement. Supply Chain Management: An International Journal. https://doi.org/10.1108/13598540010338893
  • Lopes, A. L. M., Carneiro, M. L., Schneider, A. B., & de Lima, M. V. A. (2010). Markowitz na otimização de carteiras selecionadas por Data Envelopment Analysis–DEA. Gestão e Sociedade, 4(9), 640-656.
  • Lopes, A. L., Lanzer, E., & Lima, M. V. (2006). Avaliação do desempenho de carteiras de ações selecionadas pelo modelo de análise envoltória de dados-DEA. Anais do 19o Congresso da APIMEC - Associação dos Analistas e Profissionais de Investimento do Mercado de Capitais. (Vol. 19). http://icase.itarget.com.br/tra/arquivos/apm/24.doc
  • Markowitz, H. (1952). Portfolio Selection. The Journal of Finance. Vol.7(1): pp.77-91.
  • McMullen, P. R., & Strong, R. A. (1998). Selection of mutual funds using data envelopment analysis. The Journal of Business and Economic Studies, 4(1), 1.
  • Murthı, B. P. S.; Choı, Yoon K.; Desaı, Preyas. Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach. European Journal of Operational Research, 1997, 98.2: 408-418. https://doi.org/10.1016/S0377-2217(96)00356-6
  • Panahı, M. S., Fard, M. T. T., and Yarbod, M. (2014). Portfolio Selection using Dea and Genetic Algorithm. Journal Homepage: IJMMF. COM, 1(10), 326-341.
  • Pizzatto, W., Ferreira, L., Bloot, M., Bessa, M., & de Souza Favoreto, R. (2005). Sistema integrado de planejamento e comercialização de energia. Espaço Energia, 2, 2-6.
  • Škrinjarić, T. (2014). Investment strategy on the Zagreb stock exchange based on dynamic DEA. Croatian Economic Survey, 16(1), 129-160. https://doi.org/10.15179/ces.16.1.5
  • Talluri, S. (2000). Silberman College of Business Administration, Fairleigh Dickinson University,“Data Envelopment Analysis: Models and Extensions”. Production/Operations Management Decision Line, 8.
  • Tarnaud, A. C., & Leleu, H. (2018). Portfolio analysis with DEA: Prior to choosing a model. Omega, 75, 57-76. https://doi.org/10.1016/j.omega.2017.02.003
  • Tsolas, I. E. (2014). Precious metal mutual fund performance appraisal using DEA modeling. Resources Policy, 39, 54-60 https://doi.org/10.1016/j.resourpol.2013.11.001
  • Zhou, Z., Xiao, H., Jin, Q., & Liu, W. (2018). DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure. European Journal of Operational Research, 269(1), 111-131.
  • https://www.finnet.com.tr/FinnetStore/Tr/Urun/AeHisseExpert (Erişim:06.07.2020)

Portföy Seçim Problemi Üzerine Karşılaştırma: Veri Zarflama Analizi Ve Ortalama Varyans Modeli Örneği

Yıl 2023, Cilt: 5 Sayı: 2, 122 - 139

Hatice Cenger Erkan Poyraz

Öz

Çalışma; portföy optimizasyonunda kullanılan Markowitz ortalama varyans modeli (OVM) ve veri zaraflama analizi (VZA) modelinin karşılaştırılmasına yöneliktir. Veri zarflama analizi; menkul kıymet getirilerinin birden fazla değişkenle ilişkilendirilmesine imkan tanıyan, menkul kıymet sayısı fazlalığı neticesinde hesaplama zorluğuna sebep olmayan ve fayda fonksiyonuna göre etkin sınır üzerinde bulunan portföylerin belirlenmesine imkan tanıyan ekonometrik bir yöntemdir. Çalışmada veri seti 2015-2019 yılları arasında BIST-100 Endeksi’nde sürekli işlem gören hisse senetlerinin, günlük getiri verilerinden oluşmaktadır. Ortalama varyans modeli’nin ve veri zarflama analizi uygulama sonuçları, beklenen getiri ve risk açısından iki hipotez oluşturularak test edilmiştir. Sonuç olarak VZA yöntemi ile oluşturulan etkin sınır üzerindeki portföylerin risk ve getirisinin OVM ile oluşturulan portföylerden farklı olduğu tespit edilmiştir.

Anahtar Kelimeler

Ortalama Varyans Modeli Veri Zarflama Analizi Portföy Optimizasyonu Etkin Sınır

Etik Beyan

Etik beyan raporunu gerektiren bir çalışma değildir.

Kaynakça

  • Andersen, P., Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264. https://doi.org/10.1287/mnsc.39.10.1261
  • Basso, A., & Funari, S. (2001). A data envelopment analysis approach to measure the mutual fund performance. European Journal of Operational Research, 135(3), 477-492. https://doi.org/10.1016/S0377-2217(00)00311-8
  • Biswas, S., Bandyopadhyay, G., Guha, B., Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision making framework. Decision Making: Applications in Management and Engineering, 2(2), 138-158.
  • Brown, R., O'Connor, I., Brown, R. (1997). Measurement of efficiency in not-for-profit financial intermediaries: Australian evidence. University of Melbourne, Department of Accounting and Finance.
  • Choi, Y. K., & Murthi, B. P. S. (2001). Relative performance evaluation of mutual funds: A non‐parametric approach. Journal of Business Finance & Accounting, 28(7‐8), 853-876.
  • Charnes, A., Cooper, W. W., and Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., & Rousseau, J. (1984). Sensitivity and stability analysis in DEA. Annals of Operations Research, 2(1), 139-156.
  • Chen, Z., & Lin, R. (2006). Mutual fund performance evaluation using data envelopment analysis with new risk measures. Or Spectrum, 28(3), 375-398.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281. https://doi.org/10.2307/2343100
  • Gregoriou, G. N., Sedzro, K., & Zhu, J. (2005). Hedge fund performance appraisal using data envelopment analysis. European Journal of Operational Research, 164(2), 555-571. https://doi.org/10.1016/j.ejor.2003.12.019
  • Kuosmanen, T. (2007). Performance measurement and best-practice benchmarking of mutual funds: combining stochastic dominance criteria with data envelopment analysis. Journal of Productivity Analysis, 28, 71-86.
  • Liu, J., Ding, F. Y., and Lall, V. (2000). Using data envelopment analysis to compare suppliers for supplier selection and performance improvement. Supply Chain Management: An International Journal. https://doi.org/10.1108/13598540010338893
  • Lopes, A. L. M., Carneiro, M. L., Schneider, A. B., & de Lima, M. V. A. (2010). Markowitz na otimização de carteiras selecionadas por Data Envelopment Analysis–DEA. Gestão e Sociedade, 4(9), 640-656.
  • Lopes, A. L., Lanzer, E., & Lima, M. V. (2006). Avaliação do desempenho de carteiras de ações selecionadas pelo modelo de análise envoltória de dados-DEA. Anais do 19o Congresso da APIMEC - Associação dos Analistas e Profissionais de Investimento do Mercado de Capitais. (Vol. 19). http://icase.itarget.com.br/tra/arquivos/apm/24.doc
  • Markowitz, H. (1952). Portfolio Selection. The Journal of Finance. Vol.7(1): pp.77-91.
  • McMullen, P. R., & Strong, R. A. (1998). Selection of mutual funds using data envelopment analysis. The Journal of Business and Economic Studies, 4(1), 1.
  • Murthı, B. P. S.; Choı, Yoon K.; Desaı, Preyas. Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach. European Journal of Operational Research, 1997, 98.2: 408-418. https://doi.org/10.1016/S0377-2217(96)00356-6
  • Panahı, M. S., Fard, M. T. T., and Yarbod, M. (2014). Portfolio Selection using Dea and Genetic Algorithm. Journal Homepage: IJMMF. COM, 1(10), 326-341.
  • Pizzatto, W., Ferreira, L., Bloot, M., Bessa, M., & de Souza Favoreto, R. (2005). Sistema integrado de planejamento e comercialização de energia. Espaço Energia, 2, 2-6.
  • Škrinjarić, T. (2014). Investment strategy on the Zagreb stock exchange based on dynamic DEA. Croatian Economic Survey, 16(1), 129-160. https://doi.org/10.15179/ces.16.1.5
  • Talluri, S. (2000). Silberman College of Business Administration, Fairleigh Dickinson University,“Data Envelopment Analysis: Models and Extensions”. Production/Operations Management Decision Line, 8.
  • Tarnaud, A. C., & Leleu, H. (2018). Portfolio analysis with DEA: Prior to choosing a model. Omega, 75, 57-76. https://doi.org/10.1016/j.omega.2017.02.003
  • Tsolas, I. E. (2014). Precious metal mutual fund performance appraisal using DEA modeling. Resources Policy, 39, 54-60 https://doi.org/10.1016/j.resourpol.2013.11.001
  • Zhou, Z., Xiao, H., Jin, Q., & Liu, W. (2018). DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure. European Journal of Operational Research, 269(1), 111-131.
  • https://www.finnet.com.tr/FinnetStore/Tr/Urun/AeHisseExpert (Erişim:06.07.2020)
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Finans
Bölüm Makaleler
Yazarlar

Hatice Cenger 0000-0002-5703-2201

Erkan Poyraz 0000-0002-6442-4705

Erken Görünüm Tarihi 28 Aralık 2023
Yayımlanma Tarihi
Gönderilme Tarihi 17 Ekim 2023
Kabul Tarihi 19 Kasım 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 2

Kaynak Göster

APA Cenger, H., & Poyraz, E. (2023). Portföy Seçim Problemi Üzerine Karşılaştırma: Veri Zarflama Analizi Ve Ortalama Varyans Modeli Örneği. Uluslararası Muhasebe Ve Finans Araştırmaları Dergisi, 5(2), 122-139.
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