ANALISIS PERBANDINGAN METODE SINGLE INDEX MODEL DAN STOCHASTIC DOMINANCE DALAM PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM INDEKS LQ45

Hendra Paji Rara, NIM.: 22106010060 (2026) ANALISIS PERBANDINGAN METODE SINGLE INDEX MODEL DAN STOCHASTIC DOMINANCE DALAM PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM INDEKS LQ45. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Investment is a commitment of funds or other resources made at present with the aim of obtaining profits in the future. One of the main strategies that investors can apply in making investment decisions is portfolio diversification, which is allocating funds to various assets or stocks in order to reduce risk without sacrificing the expected rate of return. The purpose of this study is to identify the stocks that make up the optimal portfolio, determine the proportion of stocks, and compare the performance of the two methods based on return, risk, and portfolio performance measures using the Single Index Model and Stochastic Dominance methods. The Single Index Model is a model for predicting security prices or returns using market indices as predictors. Meanwhile, the Stochastic Dominance method does not require the assumption of a normal distribution of returns and consists of three orders based on investor preferences. The research sample consisted of 25 stocks that were consistently listed on the LQ45 index from January 2021 to July 2025, selected using purposive sampling. The results show that the optimal portfolio based on the Single Index Model consists of INDF, BBNI, UNTR, BBCA, and ICBP stocks, with an expected return of 0.09% and a risk of 4.27%. Meanwhile, the Stochastic Dominance-based portfolio consists of INDF, BBCA, ADRO, and ITMG stocks, with an expected return of 0.10% and a risk of 3.44%. Performance evaluation shows that the Stochastic Dominance portfolio has higher Sharpe and Treynor ratios, while Jensen's alpha is relatively comparable. Considering the combination of return, risk, and portfolio performance, Stochastic Dominance is declared as the best model in this study because it produces a more efficient portfolio in terms of risk.

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