Forgiving Debt in Financial Network Games
Authors: Panagiotis Kanellopoulos, Maria Kyropoulou, Hao Zhou
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the computational hardness of finding the optimal debt-removal and budget-constrained optimal bailout policy, respectively, and we investigate the approximation ratio provided by the greedy bailout policy compared to the optimal one. We also study financial systems from a gametheoretic standpoint. We observe that the removal of some incoming debt might be in the best interest of a bank. Assuming that a bank s well-being (i.e., utility) is aligned with the incoming payments they receive from the network, we define and analyze a game among banks who want to maximize their utility by strategically giving up some incoming payments. In addition, we extend the previous game by considering bailout payments. After formally defining the above games, we prove results about the existence and quality of pure Nash equilibria, as well as the computational complexity of finding such equilibria. |
| Researcher Affiliation | Academia | University of Essex, UK {panagiotis.kanellopoulos, maria.kyropoulou, hz18065}@essex.ac.uk |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements about releasing source code or links to a code repository. |
| Open Datasets | No | The paper is theoretical and uses an illustrative example in Figure 1, but does not use or refer to any publicly available dataset for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe running empirical experiments, thus no hardware specifications are mentioned. |
| Software Dependencies | No | The paper does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not involve empirical experiments with a detailed experimental setup including hyperparameters or system-level training settings. |