Perbandingan Kinerja Hierarchical Risk Parity, Low-Risk Hierarchical Risk Parity, Dan Mean–Variance Optimization Pada Indeks Idx30

Nurfatin, Euisya Maulida (2026) Perbandingan Kinerja Hierarchical Risk Parity, Low-Risk Hierarchical Risk Parity, Dan Mean–Variance Optimization Pada Indeks Idx30. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pasar saham Indonesia memiliki karakteristik return dan risiko yang dinamis sehingga pembentukan portofolio perlu mempertimbangkan metode alokasi aset yang mampu menyesuaikan kinerja dengan profil risiko investor. Penelitian ini bertujuan untuk membandingkan kinerja portofolio saham menggunakan metode Mean–Variance Optimization (MVO), Hierarchical Risk Parity (HRP), dan Low-Risk Hierarchical Risk Parity pada saham yang tergabung dalam indeks IDX30. Data yang digunakan berupa harga penutupan mingguan 27 saham IDX30 periode Januari 2018 hingga Desember 2025. Saham diseleksi berdasarkan Sharpe ratio, kemudian dikelompokkan menjadi portofolio Top-5, Top-10, Top-15, dan Top-21. Evaluasi kinerja dilakukan menggunakan pendekatan rolling out-of-sample dengan estimation window sepanjang 260 minggu dan rebalancing setiap empat minggu. Metrik evaluasi meliputi mean return, standar deviasi, Sharpe ratio, cumulative return, maximum drawdown, Value-at-Risk (VaR), dan Conditional Value-at-Risk (CVaR). Hasil penelitian menunjukkan bahwa setiap metode memiliki karakteristik kinerja yang berbeda. HRP Top-5 menghasilkan mean return dan cumulative return tertinggi, yaitu sebesar 0,5654% dan 111,37%, sehingga lebih sesuai untuk investor agresif. Low-Risk HRP Top-15 memberikan kombinasi return dan risiko yang cukup seimbang dengan mean return 0,3506%, cumulative return 60,94%, dan maximum drawdown -23,09%, sehingga sesuai untuk investor moderat. Sementara itu, MVO Top-21 menghasilkan risiko paling rendah dengan standar deviasi 1,9969%, VaR 95% sebesar 2,9946%, dan CVaR 95% sebesar 4,0726%, sehingga lebih sesuai untuk investor konservatif. Dengan demikian, pemilihan portofolio optimal perlu mempertimbangkan metode optimasi, jumlah saham, dan profil risiko investor.
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The Indonesian stock market has dynamic return and risk characteristics, making portfolio construction important in aligning asset allocation with investors’ risk profiles. This study aims to compare the performance of stock portfolios constructed using Mean–Variance Optimization (MVO), Hierarchical Risk Parity (HRP), and Low-Risk Hierarchical Risk Parity on stocks included in the IDX30 index. The data consist of weekly closing prices of 27 IDX30 stocks from January 2018 to December 2025. Stocks are selected based on their Sharpe ratio and grouped into four portfolio sizes: Top-5, Top-10, Top-15, and Top-21. Portfolio performance is evaluated using a rolling out-of-sample approach with a 260-week estimation window and a four-week rebalancing period. The evaluation metrics include mean return, standard deviation, Sharpe ratio, cumulative return, maximum drawdown, Value-at-Risk (VaR), and Conditional Value-at-Risk (CVaR). The results show that each method has different performance characteristics. The HRP Top-5 portfolio produces the highest mean return and cumulative return, reaching 0.5654% and 111.37%, respectively, making it more suitable for aggressive investors. The Low-Risk HRP Top-15 portfolio provides a relatively balanced combination of return and risk, with a mean return of 0.3506%, cumulative return of 60.94%, and maximum drawdown of -23.09%, making it appropriate for moderate investors. Meanwhile, the MVO Top-21 portfolio produces the lowest risk, with a standard deviation of 1.9969%, VaR 95% of 2.9946%, and CVaR 95% of 4.0726%, making it more suitable for conservative investors. Therefore, optimal portfolio selection should consider the optimization method, portfolio size, and investor risk profile.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Hierarchical Risk Parity, IDX30, Low-Risk Hierarchical Risk Parity, Mean–Variance Optimization
Subjects:	H Social Sciences > HG Finance > HG4529 Investment analysis H Social Sciences > HG Finance > HG4529.5 Portfolio management H Social Sciences > HG Finance > HG4910 Investments
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Euisya Maulida Nurfatin
Date Deposited:	20 Jul 2026 01:59
Last Modified:	20 Jul 2026 01:59
URI:	http://repository.its.ac.id/id/eprint/135446

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