PENGUKURAN RISIKO KREDIT OBLIGASI KORPORASI DENGAN CREDIT VALUE AT RISK (CVAR) DAN OPTIMALISASI PORTOFOLIO MENGGUNAKAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP)

SOMANTRI, AGUS (2013) PENGUKURAN RISIKO KREDIT OBLIGASI KORPORASI DENGAN CREDIT VALUE AT RISK (CVAR) DAN OPTIMALISASI PORTOFOLIO MENGGUNAKAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP). Undergraduate thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also it gives potential risks such as credit risk. Credit risk originates from the fact that counterparties may be unable to fulfill their contractual obligations. Credit Value at Risk (CVaR) is introduced as a method to calculate bond credit risk if default occurs. CVaR is defined as the most significant credit loss which occurs unexpectedly at the selected level of confidence, measured as the deviation of Expected Credit Loss (ECL). To construct optimal bond portfolio requires Mean variance Efficient Portfolio (MVEP) method. MVEP is defined as the portfolio with minimum variance among all possible portfolios that can be formed. This study case has been constructed through two bonds, bond VI of Jabar Banten Bank (BJB) year 2009 serial B and bond of BTPN Bank I year 2009 serial B. Based on the R programming output, the obtained results for bonds with a rating idAA- BJB, has a positive CVaR value of Rp 22.728.338,00. While bonds with a rating idAA- BTPN and portfolio for both bonds, each of which has a negative CVaR value amounted Rp -28.759.098,00 and Rp -32.187.425,00. CVaR is positive (+) expressed as the loss addition of ECL while is negative (-) expressed as a decrease in loss of ECL. For optimal bond portfolio, gained weight for each bond is equal to 16,85202% for BJB and 83,14798% for BTPN bonds. Key Words : bond, credit risk, portfolio, default, Expected Credit Loss, rating, Credit Value at Risk, Mean variance Efficient Portfolio.

Item Type:Thesis (Undergraduate)
Subjects:H Social Sciences > HA Statistics
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:42340
Deposited By:Mr Hasbi Yasin
Deposited On:20 Feb 2014 09:27
Last Modified:04 Mar 2014 11:19

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