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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/75542
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75542


    Title: Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk
    Authors: Chang, Y.-P.;Yu, Chih-Tun
    游智惇
    Contributors: 統計系
    Keywords: Asset correlation;Bayesian confidence intervals;MCMC;Portfolio credit risk;Probability of default;Serial dependence
    Date: 2014-02
    Issue Date: 2015-06-03 11:17:01 (UTC+8)
    Abstract: We derive Bayesian confidence intervals for the probability of default (PD), asset correlation (Rho), and serial dependence (Theta) for low default portfolios (LDPs). The goal is to reduce the probability of underestimating credit risk in LDPs. We adopt a generalized method of moments with continuous updating to estimate prior distributions for PD and Rho from historical default data. The method is based on a Bayesian approach without expert opinions. A Markov chain Monte Carlo technique, namely, the Gibbs sampler, is also applied. The performance of the estimation results for LDPs validated by Monte Carlo simulations. Empirical studies on Standard & Poor's historical default data are also conducted. © 2013 Springer-Verlag Berlin Heidelberg.
    Relation: Computational Statistics, 29(1-2), 331-361
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1007/s00180-013-0453-2
    DOI: 10.1007/s00180-013-0453-2
    Appears in Collections:[統計學系] 期刊論文

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