Merton Model as a Tool to Detect Default Risk via Visualized Banking Network: Vietnamese Evidence
- DOI
- 10.2991/978-94-6463-348-1_16How to use a DOI?
- Keywords
- Banking networks; Distance-to-Default; Probability of Default
- Abstract
The paper investigates banking networks in Vietnam with a focus on default probability. Distance-to-Default (DD) and Conditional Probability of Default (PD) based on Merton model are used to create visualized banking networks. Some specific circumstances of Vietnamese bank network are used to test the proposed model. The results seem to be consistent with the expectations and support the model’s effectiveness. The model helps to recognize the most important banks of the banking network and to warn the problematic banks, the implications of which may be useful to policy makers. Some other testing contexts are the “Before Covid 19 context” and “the fourth wave of Covid19 context”, Vietnam’s most severe wave. Both contexts show the two distinct clusters of the banking network, may also refer to some policy implications.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Nguyen Thi Minh Hue AU - Do Phuong Huyen AU - Takuya Kaneko AU - Masato Hisakado AU - My Nguyen PY - 2024 DA - 2024/02/05 TI - Merton Model as a Tool to Detect Default Risk via Visualized Banking Network: Vietnamese Evidence BT - Proceedings of the 11th International Conference on Emerging Challenges: Smart Business and Digital Economy 2023 (ICECH 2023) PB - Atlantis Press SP - 179 EP - 193 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-348-1_16 DO - 10.2991/978-94-6463-348-1_16 ID - Hue2024 ER -