A Measurement and Treatment Method of Bond Default Risk Based on Monte Carlo Simulation Technology

DOI

10.2991/978-94-6463-198-2_76How to use a DOI?

Keywords

Monte Carlo Simulation; measurement; bond risk

Abstract

In the scenario of bank bond risk measurement, due to the scarcity of bond default sample data and feature information, the model after machine learning modeling is not enough to represent the past and predict the future, which affects the accurate measurement of bond default risk. The system uses Monte Carlo simulation based on economic and financial theory and data statistical analysis. The system realizes refined calculation and a large number of simulations of bond loss results, and effectively measures a large number of simulated loss results.

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.

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TY  - CONF
AU  - Chunyan Xue
PY  - 2023
DA  - 2023/08/10
TI  - A Measurement and Treatment Method of Bond Default Risk Based on Monte Carlo Simulation Technology
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 735
EP  - 742
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_76
DO  - 10.2991/978-94-6463-198-2_76
ID  - Xue2023
ER  -