Prediksi Portofolio Return Saham Menggunakan Modifikasi Kalman Filter

Larasati, Oktaviana (2022) Prediksi Portofolio Return Saham Menggunakan Modifikasi Kalman Filter. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Portofolio saham digunakan investor agar apabila salah satu instrumen investasinya mengalami kerugian, masih ada instrumen lainnya yang dapat diharapkan. Prediksi terhadap return portofolio harga saham merupakan hal terpenting untuk meminimumkan resiko dalam melakukan investasi saham. Sebab return portofolio dicari agar investor realistis akan investasinya. Sehingga investor tidak asal memilih saham untuk investasi. Pada penelitian ini akan dilakukan prediksi return portofolio dari data harga penutupan harian PT. Bank Central Asia (BBCA.JK) dan PT. Bank Rakyat Indonesia (BBRI.JK) pada bulan Januari 2016-desember 2020 menggunakan model terbaiknya yaitu ARMA (1,0). Kemudian dilakukan prediksi portofolio return menggunakan metode Kalman Filter dan Modifikasi Kalman Filter. Hasil dari simulasi menggunakan ARMA menghasilkan nilai RMSE sebesar 0.0876032. Untuk ARMA-Kalman Filter sembilan langkah menghasilkan nilai RMSE sebesar 0,0635276 dan Modifikasi Kalman Filter untuk sembilan langkah menghasilkan nilai RMSE sebesar 0,0854241.
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The stock portfolio is used by investors so that if one of their investment instruments suffers a loss, there are other instruments that can be expected. Prediction of stock price portfolio returns is the most important thing to minimize risk in investing in stocks. Because the return portfolio is sought so that investors are realistic about their investments. So that investors do not just choose stocks for investment. In this study, a portfolio return prediction will be made from the daily closing price data of PT. Bank Central Asia (BBCA.JK) and PT. Bank Rakyat Indonesia (BBRI.JK) in January 2016-December 2020 used the best model, namely ARMA (1.0). Then the portfolio return prediction is made using the Kalman Filter method and Modified Kalman Filter. The results of the simulation using ARMA produce an RMSE value of 0.0876032. The nine-step ARMA-Kalman Filter produces an RMSE value of 0.0635276 and the modified Kalman Filter for nine steps produces an RMSE value of 0.0854241.

Item Type:	Thesis (Other)
Additional Information:	RSMa 519.544 Lar p-1 2022
Uncontrolled Keywords:	Prediksi Return Portofolio Saham. ARMA Box-Jenkins. Modifikasi kalman Filter. RMSE (Root Mean Squared Error). Prediction of Stocks Return Portofolio Using Kalman Filter Modified. ARIMA Box-Jenkins. Kalman Filter Modified. RMSE.
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	09 Jun 2026 08:31
Last Modified:	09 Jun 2026 08:31
URI:	http://repository.its.ac.id/id/eprint/133656

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