To Measure Concentration Risk - A comparative study
(2017) FMS820 20171Mathematical Statistics
- Abstract
- Credit risk is one of the largest risks facing a bank and following the Basel regulations, banks are expected to hold capital to protect themselves against credit risk. This thesis aims to evaluate models to calculate the capital requirement for credit concentration risk and compare them to the models suggested by Finansinspektionen.
Credit concentration risk can be split into name and sector concentration and two models are evaluated for each type of concentration risk. For both name and sector concentration a Full Monte Carlo method is implemented but as this is a time consuming method, alternative methods are suggested. For name concentration risk the alternative method splits the portfolio into two sub-portfolios and treats only one... (More) - Credit risk is one of the largest risks facing a bank and following the Basel regulations, banks are expected to hold capital to protect themselves against credit risk. This thesis aims to evaluate models to calculate the capital requirement for credit concentration risk and compare them to the models suggested by Finansinspektionen.
Credit concentration risk can be split into name and sector concentration and two models are evaluated for each type of concentration risk. For both name and sector concentration a Full Monte Carlo method is implemented but as this is a time consuming method, alternative methods are suggested. For name concentration risk the alternative method splits the portfolio into two sub-portfolios and treats only one of the portfolios as if it contains any name concentration risk. The proposed method for sector concentration builds on the multi-factor Merton model and gives an analytical solution. Each pair of models is tested on separate sets of simulated portfolios containing varying degrees of name respective sector concentration. Both methods assessing name concentration perform well but as the alternative method is faster, this is to be preferred. None of the methods are in perfect agreement with the results of the methods of Finansinspektionen and although this does not necessarily indicate that the models are faulty one should investigate the reasons behind the differing results before continuing with any of the methods. When testing the sector concentration the alternative method appears to be the preferable one but as both methods differ greatly from the results of Finansinspektionen none of the methods should be used before considering the reasons for the large deviations in results. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8911760
- author
- Broström, Alma and Scheibenpflug, Hanna
- supervisor
- organization
- course
- FMS820 20171
- year
- 2017
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Multi factor adjustment, Pykhtin, Partial Portfolio Approach, capital requirement, Monte Carlo, name concentration, sector concentration, Credit concentration risk
- language
- English
- id
- 8911760
- date added to LUP
- 2017-06-07 07:52:07
- date last changed
- 2017-06-07 07:52:07
@misc{8911760,
abstract = {{Credit risk is one of the largest risks facing a bank and following the Basel regulations, banks are expected to hold capital to protect themselves against credit risk. This thesis aims to evaluate models to calculate the capital requirement for credit concentration risk and compare them to the models suggested by Finansinspektionen.
Credit concentration risk can be split into name and sector concentration and two models are evaluated for each type of concentration risk. For both name and sector concentration a Full Monte Carlo method is implemented but as this is a time consuming method, alternative methods are suggested. For name concentration risk the alternative method splits the portfolio into two sub-portfolios and treats only one of the portfolios as if it contains any name concentration risk. The proposed method for sector concentration builds on the multi-factor Merton model and gives an analytical solution. Each pair of models is tested on separate sets of simulated portfolios containing varying degrees of name respective sector concentration. Both methods assessing name concentration perform well but as the alternative method is faster, this is to be preferred. None of the methods are in perfect agreement with the results of the methods of Finansinspektionen and although this does not necessarily indicate that the models are faulty one should investigate the reasons behind the differing results before continuing with any of the methods. When testing the sector concentration the alternative method appears to be the preferable one but as both methods differ greatly from the results of Finansinspektionen none of the methods should be used before considering the reasons for the large deviations in results.}},
author = {{Broström, Alma and Scheibenpflug, Hanna}},
language = {{eng}},
note = {{Student Paper}},
title = {{To Measure Concentration Risk - A comparative study}},
year = {{2017}},
}