Estimating Loss Given Default Considering Firm’s Debt Structure and Collateral Liquidity: A Case Study of Selected Firms Listed on the Iranian Capital Market

Document Type : Original Article

Authors

1 PhD candidate in Financial Engineering, Department of Management, University of Isfahan, Isfahan, Iran

2 Assistant Professor, Department of Management, University of Isfahan, Isfahan, Iran

3 Assistant professor, Department of Mathematics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran.

Abstract

Purpose: Credit risk is the most important risk that banks are facing. Two main variables used for modeling this risk and determining the expected loss from lending are "Probability of Default" and "Loss Given Default." Given the importance of the loss-given-default (LGD) in various applications of credit risk management and credit rating, this study presents a method using the structural model approach to estimate this variable for both secured and unsecured debt, focusing on debt structure and collateral liquidity. The proposed approach has been applied to estimate the LGD for some selected firms active in the Iranian capital market.
Method: To estimate the "Expected LGD" and "Downturn LGD" for secured (with both liquid and less liquid collateral) and unsecured debts, a structural model and Monte Carlo simulation approach have been employed. In this structural model, the market value of the firm's total assets follows a Jump-Diffusion process, and each collateral, being among the firm's tangible assets, has a separate but dependent stochastic process relative to the firm's total assets. Additionally, a liquidity penalty is considered for less liquid collateral.Furthermore, in this study, different values are considered for the ratio of tangible assets to total assets in default and non-default conditions (operations). To estimate the LGD  for the debts of eleven selected eligible firms, after determining the parameters of the stochastic process for assets of each firm and collateral using data up to the end of the fiscal year 1396 (2017), the Loss Given Default for these firms' debts at the end of the fiscal year 1397 (2018) was estimated using the structural model and Monte Carlo simulation approach.In the Monte Carlo simulation, 500,000 paths for total assets and collaterals were simulated. For the paths where defaults were observed, the expected Loss Given Default values were  estimated, first at the debt level and then at the firm level. Additionally, to perform a sensitivity analysis, the mentioned variables were estimated under alternative debt structures for the same firms.
Findings: For firms with a debt structure consisting of only one secured debt, where the collateral is liquid and the debt is recovered solely from the collateral, the expected Loss Given Default values for secured debt are similar, ranging from 14% to 14.5%. If the type of collateral changes to the less liquid one, for the same firms, this value ranges from 30% to 33%. For the total LGD variable (where debt recovery comes from both collateral and other remaining assets of the firm), the average expected values for these two debt structures are 9% and 12%, respectively. For firms with a debt structure involving two secured debts, the expected LGD values, where recovery is solely from collateral, are similar to those of firms with only one secured debt with the same type of collateral. However, the average expected total LGD for secured debt with liquid collateral is 10%, and for less liquid collateral, it is 15.8%. Additionally, as the proportion of secured debts with liquid collateral relative to total debts decreases, the expected LGD at the firm level tends to increase on average. Moreover, in the downturn, the LGD for secured debt with liquid collateral is less influenced by the debt structure and is primarily affected by the dynamics of assets and collateral and the values of these two variables under critical conditions.
Conclusion: In this study, the LGD for debts was estimated using a structural model and through Monte Carlo simulation for the debts of eleven selected firms listed on the Tehran Stock Exchange. Considering two types of collateral with different liquidity and three common debt structures of companies, it was determined that the liquidity of collateral plays a significant role in reducing the expected LGD for secured loans. The role of debt structure, given the priority of secured debt payments, affects the amount of LGD for unsecured debt, as well as the total LGD for secured debts and the total LGD at the firm level.

Keywords

References

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Financial Management Perspective
Volume 14, Issue 45
2024
Pages 85-122

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