Data mining procedures in generalized Cox regressions
Zhen Wei
A chapter in Econometrics and Risk Management, 2008, pp 159-194 from Emerald Group Publishing Limited
Abstract:
Survival (default) data are frequently encountered in financial (especially credit risk), medical, educational, and other fields, where the “default” can be interpreted as the failure to fulfill debt payments of a specific company or the death of a patient in a medical study or the inability to pass some educational tests. This paper introduces the basic ideas of Cox's original proportional model for the hazard rates and extends the model within a general framework of statistical data mining procedures. By employing regularization, basis expansion, boosting, bagging, Markov chain Monte Carlo (MCMC) and many other tools, we effectively calibrate a large and flexible class of proportional hazard models. The proposed methods have important applications in the setting of credit risk. For example, the model for the default correlation through regularization can be used to price credit basket products, and the frailty factor models can explain the contagion effects in the defaults of multiple firms in the credit market.
Date: 2008
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.101 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.101 ... d&utm_campaign=repec (application/pdf)
https://www.emerald.com/insight/content/doi/10.101 ... 0731-9053(08)22007-4
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(08)22007-4
DOI: 10.1016/S0731-9053(08)22007-4
Access Statistics for this chapter
More chapters in Advances in Econometrics from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().