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Stochastic volatility and early warning indicator

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2020) 12137 LNCS 413-421
DOI: 10.1007/978-3-030-50371-0_30
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Abstract

We extend Merton’s framework by adopting stochastic volatility to propose an early warning indicator for banks’ credit risk. Bayesian inference is employed to estimate the parameters of Heston model. We provide empirical evidence and demonstrate the comparative strength of our risk measure over others.

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Ji, G., Kong, H., Kim, W. C., & Ahn, K. (2020). Stochastic volatility and early warning indicator. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12137 LNCS, pp. 413–421). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-50371-0_30

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