Journals / Yaşar Üniversitesi E-Dergisi / 2022 / Cilt: 17 - Sayı: 65

Portfolio Diversification and Optimization at Industry Level, Evidence from Turkey

Sektör Düzeyinde Portföy Çeşitlendirmesi ve Portföy Optimizasyonu, Türkiye Uygulaması

Pages
277–294
Publication Date
2022-01-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Portfolio optimization analysis indicates that the wholesale, retail trade and transportation industries should be prioritized by the policymakers, as these industries earn the highest returns at a given risk level.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper applies the mean-variance, mean-VaR, and mean-CVaR portfolio optimization approach to investigate opportunities for domestic diversification from Turkey investors’ viewpoints.
📊
Key Findings & Data:We explore diversification potential and investment opportunities at the industry level for the time period between 2007 and 2020.
💡
Conclusion & Impact:Portfolio optimization analysis indicates that the wholesale, retail trade and transportation industries should be prioritized by the policymakers, as these industries earn the highest returns at a given risk level.
🔬Design:Modeling & Simulation
📍Scope:2007 Verileri
⚙️Variables:Portföy optimizasyonu · faktör analizi · yurtiçi çeşitlendirme

Abstract

This paper applies the mean-variance, mean-VaR, and mean-CVaR portfolio optimization approach to investigate opportunities for domestic diversification from Turkey investors’ viewpoints. We explore diversification potential and investment opportunities at the industry level for the time period between 2007 and 2020. The study uses factor analysis to determine domestic diversification opportunities and measure the optimal weight of sectors in the market index. Results from factor analysis show that for investors who desire to create a domestic portfolio considerable diversification opportunities are available. Portfolio optimization analysis indicates that the wholesale, retail trade and transportation industries should be prioritized by the policymakers, as these industries earn the highest returns at a given risk level.

Özet

This paper explores diversification potential and investment opportunities at the industry level for Turkey for the time period between 2007 and 2020. This study uses the factor analysis to determine domestic diversification opportunities and the Markowitz's risk-return model to evaluate portfolio optimization and measure the optimal weight of sectors in the market index. Results show that the wholesale, retail trade and transportation industries should be prioritized by the policy makers, as these industries earn highest returns at a given risk level. Bu çalışma 2007 ve 2020 yılları arasında Türkiye’de sektör düzeyinde çeşitlendirme potansiyelini ve yatırım fırsatlarını incelemektedir. Bu çalışma, yurtiçi çeşitlendirme fırsatlarını belirlemek için faktör analizini ve portföy optimizasyonunu değerlendirmek ve piyasa endeksindeki sektörlerin optimum ağırlığını ölçmek için Markowitz’in risk-getiri modelini kullanmaktadır. Yazarlar toptan ve perakende ticaret, taşıma ve ulaşım sektörlerin siyasete yön verenler tarafından öncelik verilmesi gerektiğini ortaya koymaktadır. Bu sektörlerin belirli bir risk seviyesinde en yüksek getiriye sahip oldukları gözlemlenmektedir.

🔖

Cite This Article

AZİMOVA, T. (2022). Portfolio Diversification and Optimization at Industry Level, Evidence from Turkey. Yaşar Üniversitesi E-Dergisi, Cilt: 17 - Sayı: 65, 277–294. https://ajindex.com/articles/422129

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. Akyuwen, R., Boffey, R. R., Powell, R. J., & Wijaya, K. (2017).Optimizing the industry mix of Indonesian portfolios. KINERJA, 18(2), 101-114.
  2. Allen, D., Kramadibrata, A., Powell, R., & Singh, A. (2012). Conditional value at risk applications to the global mining industry. Journal of Business and Policy Research, 7(3), 11-23.
  3. Allen, D., & Powell, R. (2011). Measuring and optimising extreme sectoral risk in Australia. Asia Pacific Journal of Economics and Business, 15(1), 1-14.
  4. Al Janabi, M. A. (2014). Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects. Economic Modelling, 40(3), 369-381.
  5. Alexander, G. J., & Baptista, A. M. (2002). Economic implications of using a mean-VaR model for portfolio selection: A comparison with meanvariance analysis. Journal of Economic Dynamics and Control, 26(7), 1159-1193.
  6. Anderson, T. W. and H. Rubin (1956). Statistical inference in factor analysis, 2nd edition, University of California Press.
  7. Akyuwen, R., Boffey, R. R., Powell, R. J., &Wijaya, K. (2017). Optimizing the industry mix of Indonesian portfolios. KINERJA, 18(2), 101-114.
  8. Artzner, P., Delbaen, F., Eber, J. M., & Heath, D. (1999). Coherent measures of risk. Mathematical finance, 9(3), 203-228.
  9. Bali, T. G. & Engle, R. F. (2010).The intertemporal capital asset pricing model with dynamic conditional correlations. Journal of Monetary Economics, 57(4), 377-390.
  10. Brandt, M. W. & Kang, Q. (2004). On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach. Journal of Financial Economics, 72(2), 217-257.
  11. Chen, R., & Yu, L. (2013). A novel nonlinear value-at-risk method for modeling risk of option portfolio with factor mixture of normal distributions. Economic Modelling, 35(4), 796-804.
  12. Campbell, R., Huisman, R., &Koedijk, K. (2001). Optimal portfolio selection in a Value-at-Risk framework. Journal of Banking & Finance, 25(9), 1789-1804.
  13. Donald R. Lessard (2008). International portfolio diversification: A factor analysis for a group of Latin American Countries. The Journal of Finance, 28 (3), 619-633.
  14. Duc Hong Vo, Thach Ngoc Pham, TrungThanh Vu Pham, Loc Minh Truong, Thang Cong Nguyen (2018). Risk, return and portfolio optimization for various industries in the ASEAN region, Borsa Istanbul Review, 19(2), 132-138.
  15. Dziuban, C. D. and E. C. Shirkey (1974). When is a correlation matrix appropriate for factor analysis, Psychological Bulletin, 81(6), 358–361. Eduard