Atika Oktavia, NIM.: 21106010064 (2025) ANALISIS RISIKO PORTOFOLIO OPTIMAL MAXIMUM SHARPE RATIO MENGGUNAKAN PERHITUNGAN CONDITIONAL VALUE AT RISK (CVAR) DENGAN METODE VARIANCE-COVARIANCE DAN MONTE CARLO (STUDI KASUS: SAHAM PERUSAHAAN SEKTOR ENERGI YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) UNTUK PERIODE DESEMBER 2019 - DESEMBER 2024). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.
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Text (ANALISIS RISIKO PORTOFOLIO OPTIMAL MAXIMUM SHARPE RATIO MENGGUNAKAN PERHITUNGAN CONDITIONAL VALUE AT RISK (CVAR) DENGAN METODE VARIANCE-COVARIANCE DAN MONTE CARLO (STUDI KASUS: SAHAM PERUSAHAAN SEKTOR ENERGI YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) U)
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Text (ANALISIS RISIKO PORTOFOLIO OPTIMAL MAXIMUM SHARPE RATIO MENGGUNAKAN PERHITUNGAN CONDITIONAL VALUE AT RISK (CVAR) DENGAN METODE VARIANCE-COVARIANCE DAN MONTE CARLO (STUDI KASUS: SAHAM PERUSAHAAN SEKTOR ENERGI YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) U)
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Abstract
Risk measurement in portfolio management can be done using various tools such as Value at Risk (VaR) and Conditional Value at Risk (CVaR), where CVaR addresses the weaknesses of VaR by taking into account losses beyond the VaR limit for a more comprehensive risk estimate. This study measures the risk of the optimal Maximum Sharpe Ratio portfolio for energy sector stocks on the IDX for the period 2019–2024 with a composition of 63.01% PTBA.JK, 13.94% MBAP.JK, and 23.05% MEDC.JK, resulting in an expected return of 1.2028% and a risk of 8.8012% per month. The CVaR value at a 95% confidence level is 16.9515 (Variance-Covariance) and 16.9095 (Monte Carlo), and at 99% it is 22.2542 and 21.9609, indicating that the estimated maximum loss exceeds the VaR. The backtesting results and Kupiec test confirm that both methods are valid in measuring portfolio risk.
| Item Type: | Thesis (Skripsi) |
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| Additional Information / Supervisor: | Dr. Epha Diana Supandi, S.Si., M.Sc. |
| Uncontrolled Keywords: | Conditional Value at Risk (CVaR), Maximum Sharpe Ratio, Monte Carlo, Portofolio Optimal, Variance-Covariance |
| Subjects: | 500 Sains Murni > 510 Mathematics (Matematika) |
| Divisions: | Fakultas Sains dan Teknologi > Matematika (S1) |
| Depositing User: | Muh Khabib, SIP. |
| Date Deposited: | 11 Jul 2025 15:31 |
| Last Modified: | 11 Jul 2025 15:31 |
| URI: | http://digilib.uin-suka.ac.id/id/eprint/71778 |
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