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Abstract
Investment in the capital market is increasingly popular among Indonesians for financial management and achieving financial goals. Bonds, offering fixed income, are a favored instrument but carry credit risk, such as issuer default. The KMV Merton model measures bond credit risk using the Expected Default Frequency (EDF), derived from the distance to default (DD). This model integrates the company’s total asset value, equity, and liabilities, providing predictive capabilities. Enhancements to asset value predictions can be made using Monte Carlo simulations, enabling more accurate forecasts across varying scenarios and improving credit risk projections. This study focuses on Sustainable Bonds IV Panin Bank Phase II of 2024, with a face value of IDR 3.91 trillion and a five-year term. A total of 900,000 simulations achieved convergence in the average total asset value with a MAPE of 1.99000456%. The EDF value without asset prediction was 2.84799919E-133 for 2024, while predictions yielded EDFs of 6.33200783E-191 for 2025, 4.45799925E-254 for 2026, and 0.00 for 2027 and 2028. The results showed an almost negligible default risk for all predicted periods, highlighting the robustness of the bond’s credit profile.
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References
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