PENERAPAN SECOND-ORDER CONE PROGRAMMING (SOCP) DALAM MENENTUKAN PORTOFOLIO OPTIMAL MODEL MEAN VARIANCE

Ani Herniawati, NIM. 14610014 (2018) PENERAPAN SECOND-ORDER CONE PROGRAMMING (SOCP) DALAM MENENTUKAN PORTOFOLIO OPTIMAL MODEL MEAN VARIANCE. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Mean variance portfolio model is the most popular portfolio model. The weakness of this model is when a sample estimation error occurs, because it can cause an unstable estimator. It will result in an inconsistent portfolio weight. The mean variance model is also very sensitive toward the changes in input parameters. Robust portfolio optimization is a portfolio that is able to overcome the problem of sensitivity on the mean variance method. In this optimization of robust portfolio, the input parameters are considered uncertain (uncertainly set). How to works this method by determining the uncertainly set in the worst case, namely the minimum portfolio return and maximum portfolio risk. The case will be brought into the form of second-order cone programming (SOCP) that finished by using interior primal dual method. This method was applied to form an optimal portfolio of stocks listed in the Jakarta Islamic Index (JII). The results showed that the coefficient value of risk aversion 5 for reurn of SOCP portfolio was 0.05%, meanwhile for return of MV portfolio was 0.11%. So that, the MV portfolio return value was higher than SOCP portfolio whit the risk value was not so far different and MV portfolio work value was better. However when it was observed again of 20 recently observation by using the closed price stock, SOCP daily profit value was far better than MV portfolio. The data was the average for SOCP daily profit of the coefficient value of risk aversion 5 was Rp3,322,325,-. The average of MV portfolio profit was -Rp16,656,975,-. So that, in the worst case of SOCP portfolio could optimize the situation and get the optimal result.

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