A new approach to measure systemic risk: A bivariate copula model for dependent censored data
| Autor: | Silvia Angela Osmetti, Raffaella Calabrese |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Empirical data
Information Systems and Management General Computer Science 0211 other engineering and technologies 02 engineering and technology Bivariate analysis Censored sampling Management Science and Operations Research Industrial and Manufacturing Engineering Copula (probability theory) systemic risk 0502 economics and business Econometrics Systemic risk Bank failure Mathematics OR in banking 050210 logistics & transportation 021103 operations research 05 social sciences copula models Estimator Copula models censored sampling Settore SECS-S/01 - STATISTICA Modeling and Simulation Pseudo-maximum likelihood estimation Bootstrap confidence interval pseudo-maximum likelihood estimation |
| Zdroj: | Calabrese, R & Osmetti, S A 2019, ' A new approach to measure systemic risk : A bivariate copula model for dependent censored data ', European Journal of Operational Research, vol. 279, no. 3, pp. 1053-1064 . https://doi.org/10.1016/j.ejor.2019.06.027 |
| DOI: | 10.1016/j.ejor.2019.06.027 |
| Popis: | We propose a novel approach based on the Marshall–Olkin (MO) copula to estimate the impact of systematic and idiosyncratic components on cross-border systemic risk. To use the data on non-failed banks in the suggested method, we consider the time to bank failure as a censored variable. Therefore, we propose a pseudo-maximum likelihood estimation procedure for the MO copula for a Type I censored sample. We derive the log-likelihood function, the copula parameter estimator and the bootstrap confidence intervals. Empirical data on the banking system of three European countries (Germany, Italy and the UK) shows that the proposed censored model can accurately estimate the systematic component of cross-border systemic risk. |
| Databáze: | OpenAIRE |
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