Document Type Master's Dissertation Author Bodvin, Liesbeth Joanna Sylvia email@example.com URN etd-07102010-123814 Document Title Bayesian estimation of Shannon entropy for bivariate beta priors Degree MSc Department Statistics Supervisor
Advisor Name Title Prof A Bekker Committee Chair Prof J J J Roux Committee Co-Chair Keywords
- Bayesian estimation
- credit risk
- probability of default
- Shannon entropy
- bivariate beta
Date 2010-09-02 Availability unrestricted Abstract
Having just survived what is arguably the worst financial crisis in time, it is expected that the focus on regulatory capital held by financial institutions such as banks will increase significantly over the next few years. The probability of default is an important determinant of the amount of regulatory capital to be held, and the accurate calibration of this measure is vital. The purpose of this study is to propose the use of the Shannon entropy when determining the parameters of the prior bivariate beta distribution as part of a Bayesian calibration methodology. Various bivariate beta distributions will be considered as priors to the multinomial distribution associated with rating categories, and the appropriateness of these bivariate beta distributions will be tested on default data. The formulae derived for the Bayesian estimation of Shannon entropy will be used to measure the certainty obtained when selecting the prior parameters.
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Please cite as follows:
Bodvin, LJS 2010, Bayesian estimation of Shannon entropy for bivariate beta priors, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-07102010-123814/ >C10/529/gm
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