TY  - JOUR
ID  - digilib37242
UR  - http://www.pphmj.com
IS  - 3
A1  - Supandi, Epha Diana
A1  - Rosadi, Dedi
A1  - Abdurakhman, Abdurakhman
N2  - Error estimation in both the expected returns and the covariance matrix hamper the construction of optimal mean-variance portfolio model. In order to overcome this problem, we consider the class of proportional type estimators. The sensitivity of the proposed estimators to errors is measured by the expected loss function (the risk function). The simulation study is conducted when multivariate returns are normally distributed and serially independent. Furthermore, simulation study is complemented by an investigation of the ex post excess returns for empirical datasets, i.e., average, standard deviation, Sharpe ratio, and utility. It turns out that the unbiased proportional estimator and the maximum likelihood estimator are underperformed compared to ?the dominant? estimator.
VL  - 101
TI  - THE OPTIMAL PORTFOLIO WEIGHTS USING THE PROPORTIONAL TYPE ESTIMATORS
AV  - public
EP  - 657
N1  - Prof Dedi Rosadi, Ph.D. UGM. Yogyakarta. Indonesia
Dr. Abdurakhman, M.Si. UGM. Yogyakarta. Indonesia
Y1  - 2017/07/01/
PB  - Pushpa Publishing House, Allahabad, India
JF  - Far East Journal of Mathematical Sciences
KW  - Portfolio
KW  -  error estimation
KW  -  loss function
SN  - ISSN: 0972-0871
SP  - 643
ER  -