Analisis Perbandingan Kinerja Perhitungan Value At Risk Berdasarkan Copula Dan Vine-Copula Pada Portofolio Optimal IDX30

Ambarita, Christian August Hamonangan (2025) Analisis Perbandingan Kinerja Perhitungan Value At Risk Berdasarkan Copula Dan Vine-Copula Pada Portofolio Optimal IDX30. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Manajemen risiko sangatlah penting dalam mengelola suatu portofolio saham, khususnya dalam menghadapi kondisi pasar yang bervolatilitas tinggi. Salah satu metode yang sering dan dapat digunakan untuk mengestimasi potensi kerugian maksimum portofolio dalam periode tertentu adalah Value at risk (VaR). Namun, pendekatan tradisional untuk mendapatkan nilai Value at Risk sering kali tidak mampu menangkap struktur dependensi yang kompleks antar aset. Untuk mengatasi hal tersebut, digunakan pendekatan copula dan vine-copula yang lebih fleksibel dalam memodelkan ketergantungan antar return saham. Portofolio dibentuk menggunakan metode Minimum Variance Portfolio untuk mendapatkan portofolio optimal dengan risiko minimum. Penelitian ini menggunakan data saham bulanan dari perusahaan yang selalu terdaftar dalam indeks IDX30 pada periode Januari 2018 hingga Januari 2025. Hasil penelitian menghasilkan bobot tiap saham berdasarkan Penilaian Capital Asset Pricing Model dan Minimum Variance Portofolio adalah 23,01% BBCA.JK, 14,1% BBNI.JK, 35,39% BBRI.JK, dan 27,5% BMRI.JK dengan risiko portofolio sebesar 5,25%. Value at risk dalam portofolio diestimasi menggunakan simulasi monte carlo dari copula menghasilkan Value at risk pada tingkat kepercayaan 99% sebesar 11,37% dan 6,1% untuk tingkat kepercayaan 90% sedangkan pada vine-copula didapatkan Value at risk pada tingkat kepercayaan 99% sebesar 12,63% dan 6,03% untuk tingkat kepercayaan 90%. Hasil uji backtesting terhadap value at risk tersebut juga menyatakan bahwa metode copula dan vine-copula dapat mengestimasi value at risk yang bersifat independen dan memiliki proporsi jumlah pelanggaran value at risk yang tidak berlebihan.
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Risk management is a very important aspect when managing a stock portfolio, especially in facing highly volatile market conditions. One commonly used method to estimate the potential maximum loss of a portfolio over a certain period is Value at Risk (VaR), but traditional approaches often fail to capture the complex dependency structure between assets. To address this limitation, more flexible methods such as copula and vine-copula are used to model the relationships between stock returns. In this study, the portfolio is constructed using the Minimum Variance Portfolio method to achieve an optimal portfolio with minimum risk, based on monthly stock data from companies consistently listed in the IDX30 index from January 2018 to January 2025. The optimal stock weights obtained using the Capital Asset Pricing Model and Minimum Variance Portfolio method are 23.01% for BBCA.JK, 14.1% for BBNI.JK, 35.39% for BBRI.JK, and 27.5% for BMRI.JK, with a total portfolio risk of 5.25%. VaR is estimated using Monte Carlo simulation based on copula, resulting in a VaR of 11.37% at the 99% confidence level and 6.1% at the 90% level, while the vine-copula approach yields a VaR of 12.63% and 6.03% at the same respective levels. Backtesting results show that both copula and vine-copula methods provide independent and reasonable VaR estimates, with violation rates that remain within acceptable limits.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Copula, CAPM, Mean-Variance Optimization, Vine-Copula,Value at risk.
Subjects:	H Social Sciences > HG Finance > HG4529.5 Portfolio management Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Christian August Hamonangan Ambarita
Date Deposited:	24 Jul 2025 02:35
Last Modified:	24 Jul 2025 02:35
URI:	http://repository.its.ac.id/id/eprint/120427

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