Marliana, Zahra Dian (2024) Pembentukan Portofolio Optimal Model Black-Litterman dengan Pendekatan Pandangan Investor Menggunakan Model ARIMA pada Saham IDX30. Other thesis, Institut Tekonologi Sepuluh Nopember.
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Abstract
Fisher Black dan Robert Litterman mengidentifikasi masalah kompleks dalam mengoptimalkan alokasi aset, termasuk kesulitan memprediksi return dan sensitivitas terhadap asumsi sehingga mereka mengembangkan model Black-Litterman yang mengintegrasikan data dari CAPM dan pandangan investor untuk memperkirakan return yang diharapkan. Model ini juga menggabungkan informasi pasar dengan pandangan investor, mengatasi masalah estimasi return, dan memperhitungkan ketidakpastian dalam pembentukan portofolio optimal. Penelitian ini menggunakan data saham bulanan perusahaan yang konsisten masuk dalam indeks IDX30 dalam periode Februari 2017 – Januari 2024 dan model ARIMA dalam pendekatan pandangahn investornya. Hasil penelitian menghasilkan nilai expected return untuk masing-masing aset sebesar 2,733% untuk ADRO.JK, 1,435% untuk BBCA.JK, 1,584% untuk BBRI.JK, 2,214% untuk KLBF.JK, 2,217% untuk SMGR.JK, dan 3,264% untuk TLKM.JK. Portofolio Black-Litterman menghasilkan nilai expected return sebesar 2,21% dengan risiko portofolio sebesar 0,214%. Dalam pengukuran risiko portofolio, penelitian ini menggunakan nilai VaR dan CVaR. CVaR digunakan untuk mengetahui ekspetasi nilai kerugian di atas VaR. Semakin besar tingkat kepercayan yang digunakan, semakin besar pula estimasi kerugian maksimum nya. Dalam penelitian ini, peneliti menggunakan tingkat kepercayaan terbesar sebesar 99% menghasilakan nilai VaR sebesar 8,76% dan nilai CVaR untuk portofolio sebesar 9,41% Hasil pengukuran kinerja portofolio metode menghasilkan nilai Sharpe ratio sebesar 0,392536137, menandakan return yang baik dibandingkan risiko. Treynor ratio sebesar 0,021070778 menunjukkan portofolio menguntungkan untuk risiko sistematis. Jensen ratio sebesar 0,017933674 menunjukkan kinerja portofolio lebih baik dari expected return menurut model CAPM.
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Fisher Black and Robert Litterman identified complex problems in optimizing asset allocation, including the difficulty of predicting returns and sensitivity to assumptions. They developed the Black-Litterman model, which integrates data from CAPM and investor views to estimate expected returns. This model also combines market information with investor views, addressing issues of return estimation and accounting for uncertainty in forming an optimal portfolio. This study uses monthly stock data of companies consistently listed in the IDX30 index during the period from February 2017 to January 2024 and employs the ARIMA model in its approach to investor views. The results of the study indicate the expected returns for each asset are 2,733% for ADRO.JK, 1,435% for BBCA.JK, 1,584% for BBRI.JK, 2,217% for KLBF.JK, 3,264% for SMGR.JK, and 1,494% for TLKM.JK. The Black-Litterman portfolio yields an expected return of 2,21% with a portfolio risk of 0,214%. In measuring portfolio risk, this study uses VaR and CVaR values. CVaR is used to determine the expected loss value above VaR. The higher the confidence level used, the greater the estimated maximum loss. In this study, the researcher used the highest confidence level of 99%, resulting in a VaR value of 8,76% and a CVaR value of 9,41% for the portfolio. The performance measurement results for the portfolio using the Sharpe method yielded a Sharpe ratio of 0,392536137, indicating a good return compared to the risk. The Treynor ratio of 0,021070778 shows the portfolio is profitable for systematic risk. The Jensen ratio of 0,017933674 indicates that the portfolio's performance is better than the expected return according to the CAPM model.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | ARIMA, Black-Litterman, Conditional Value at Risk, Return, Value at Risk |
Subjects: | H Social Sciences > H Social Sciences (General) > H61.4 Forecasting in the social sciences H Social Sciences > HG Finance > HG4529.5 Portfolio management H Social Sciences > HG Finance > HG4915 Stocks--Prices |
Divisions: | Faculty of Mathematics, Computation, and Data Science > Actuaria > 94203-(S1) Undergraduate Thesis |
Depositing User: | Zahra Dian Marliana |
Date Deposited: | 31 Jul 2024 13:34 |
Last Modified: | 31 Jul 2024 13:34 |
URI: | http://repository.its.ac.id/id/eprint/110605 |
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