OPTIMASI PORTOFOLIO MULTIOBJEKTIF BERDASARKAN PREDIKSI HARGA SAHAM DENGAN MODEL ARIMA

Shofia Nur Fadhila, NIM.: 18106010003 (2022) OPTIMASI PORTOFOLIO MULTIOBJEKTIF BERDASARKAN PREDIKSI HARGA SAHAM DENGAN MODEL ARIMA. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

ARIMA is a time series method that is used to predict data. Stock price data has a non-stationary pattern because of the spirit of changing stock price movements. Invest in assets like In addition to making profits, stocks must also face risks. Portfolio formation needs to be done to minimize risk. Multi-objective optimization is one method of forming a portfolio that has the aim of maximize return and minimize risk at the same time. Destination of this research is to find out the steps of the ARIMA model and multi-objective model, to determine the accuracy of the ARIMA model prediction, and to find out the proportion of each stock formed from the model multi-objective. The research method used is quantitative descriptive method which is applied to the closing data of the monthly share price of PT. Aneka Tambang, PT. Indofood CBP Sukses Makmur, and PT. United Tractors. The results of the this study shows that the best model for forecasting ANTM’s stock prices is is ARIMA ([1],2,[2]) with a MAPE value of 32,286, ICBP’s are ARIMA (0,1,[2]) with a MAPE value of 12,139, and UNTR’s are ARIMA (0.2,[2]) with a MAPE value of 30,015. The optimal portfolio for risk seeker type investors is by choosing γ = 0.01 by investing 87% of ANTM shares, 2% of ICBP’s shares, and 11% of UNTR’s shares. Optimal portfolio for type investors risk indifference is to choose a weighting value of 1 < γ < 100 and a portfolio The optimal lio that is formed for risk averse investors is to choose the value of γ > 100.

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