Abstract
Bu çalışmada Özdemir ve Giresunlu [1] tarafından önerilen algoritma, farklı piyasalardan yatırımcıların riske karşı tutumlarının karşılaştırılması amacıyla, yabancı hisse senetleri piyasaları ile birlikte İstanbul Menkul Kıymetler Borsası Ulusal-100 endeksine ait hisse senetlerine uygulanmıştır. Kesirli programlama ile riskten kaçınma katsayısı için bir minimum değer elde edilmiş, bu
değere karşılık gelen portföylerin minimum riskli portföyler olduğu gösterilerek farklı piyasalar için riskten kaçınma katsayısının minimum değeri hesaplanmıştır. Farklı piyasalardaki yatırımcıların riske karşı tutumları, riskten kaçınma katsayısı baz alınarak piyasalar riskliliklerine göre sıralanmıştır. Sıcak para akımlarının neden Türk piyasalarını tercih ettiği sorusu bu bağlamda cevaplandırılmıştır.
References
- Risk Aversion Constant. Physics, Mathematics, Journal “Knowledge”, “Education Society of Azerbaijan Republic. 2: 61-66 (2004).
- Markowitz H., Portfolio Selection. Journal of Finance. 7(1): 77–91 (1952).
- Portfolio Selection Problems. Management Science. 29(11): 1257–1276 (1983).
- Arrow K.J., Essays on the Theory of Risk Bearing, Markhami, Chicago, 1971. ), January-April: 122–136 (1964).
- Algortihms, Second Edition. John Wiley and Sons, Inc., Singapore, 1993.
- Stock Portfolios And Capital Budgets. Review of Economics and Statistics. 47: 13–37 (1965).
- Journal of Portfolio Management. Summer: 71–81 (2001). Science.13(7): 492–498 (1967). W. On Nonlinear Fractional Programming. Management Appendix A
- Figure 1: Efficient frontier Efficient Frontier 002 001 002 003 004 V(x) 007 008 Figure 2: Utility functions for different investors Utility functions 02 0026206 0038172 0031906 E(x) 0031244 0031237
- Figure 3: F() function for various values F(Lambda) function 0.0005 Lambda DJI EuroStoxx Hang-Seng XU100
Abstract
This paper applies the algorithm proposed by Özdemir and Giresunlu [1] to the foreign stock markets as well as Istanbul Stock Exchange National-100 index and its constituent stocks in order to address the risk perceptions of investors from different markets. An optimal value of the risk aversion constant, which corresponds to the minimum risky portfolio for each market is obtained by using fractional programming and the risk level of different markets are compared based on the risk aversion constant calculated. Stock markets are ordered according to the investors’ risk-bearing attitude. The question of why the hot capital flows prefer Turkish market is answered in this context.
References
- Risk Aversion Constant. Physics, Mathematics, Journal “Knowledge”, “Education Society of Azerbaijan Republic. 2: 61-66 (2004).
- Markowitz H., Portfolio Selection. Journal of Finance. 7(1): 77–91 (1952).
- Portfolio Selection Problems. Management Science. 29(11): 1257–1276 (1983).
- Arrow K.J., Essays on the Theory of Risk Bearing, Markhami, Chicago, 1971. ), January-April: 122–136 (1964).
- Algortihms, Second Edition. John Wiley and Sons, Inc., Singapore, 1993.
- Stock Portfolios And Capital Budgets. Review of Economics and Statistics. 47: 13–37 (1965).
- Journal of Portfolio Management. Summer: 71–81 (2001). Science.13(7): 492–498 (1967). W. On Nonlinear Fractional Programming. Management Appendix A
- Figure 1: Efficient frontier Efficient Frontier 002 001 002 003 004 V(x) 007 008 Figure 2: Utility functions for different investors Utility functions 02 0026206 0038172 0031906 E(x) 0031244 0031237
- Figure 3: F() function for various values F(Lambda) function 0.0005 Lambda DJI EuroStoxx Hang-Seng XU100
Details
| Primary Language | English |
|---|---|
| Journal Section | Finance |
| Authors | |
| Publication Date | December 5, 2007 |
| Published in Issue | Year 2008 Volume: 37 Issue: 1 |
