Robustness Analysis when Estimating Economic Capital for Credit Risk
(2016) FMS820 20161Mathematical Statistics
 Abstract
 Credit risk modeling is an important part of the nancial protection used by banks during
times of turbulence in the economy. More precisely, the modelling is about estimating
how much economic capital a bank needs to hold in order to survive during an extreme
loss. This thesis is about improving the robustness for the estimation of the economic
capital, when it is updated as time passes. A decrease of the variations in the estimate of
the economic capital would allow the bank to decrease the frequency of which the value
of the economic capital is updated. This is the main aim for the thesis, as banks have a
hard time explaining these variations based on any logical ground. The model used for
estimating the economic capital is based... (More)  Credit risk modeling is an important part of the nancial protection used by banks during
times of turbulence in the economy. More precisely, the modelling is about estimating
how much economic capital a bank needs to hold in order to survive during an extreme
loss. This thesis is about improving the robustness for the estimation of the economic
capital, when it is updated as time passes. A decrease of the variations in the estimate of
the economic capital would allow the bank to decrease the frequency of which the value
of the economic capital is updated. This is the main aim for the thesis, as banks have a
hard time explaining these variations based on any logical ground. The model used for
estimating the economic capital is based on a multifactor Merton model. The study will
look at how the correlation matrix of the factors in the model can be updated in order
to obtain as little variation as possible for the estimate of the economic capital. Four
major approaches will be conducted to try and minimize this variation. The approaches
use techniques such as weighting of consecutive correlation matrices, bootstrapping and
standardization of the data using a multivariate CCC GARCH model. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/8891072
 author
 Tellqvist, Ella and Kustvall Larsson, Martin
 supervisor

 Magnus Wiktorsson ^{LU}
 organization
 course
 FMS820 20161
 year
 2016
 type
 H2  Master's Degree (Two Years)
 subject
 language
 English
 id
 8891072
 date added to LUP
 20160907 15:14:37
 date last changed
 20160907 15:14:37
@misc{8891072, abstract = {Credit risk modeling is an important part of the nancial protection used by banks during times of turbulence in the economy. More precisely, the modelling is about estimating how much economic capital a bank needs to hold in order to survive during an extreme loss. This thesis is about improving the robustness for the estimation of the economic capital, when it is updated as time passes. A decrease of the variations in the estimate of the economic capital would allow the bank to decrease the frequency of which the value of the economic capital is updated. This is the main aim for the thesis, as banks have a hard time explaining these variations based on any logical ground. The model used for estimating the economic capital is based on a multifactor Merton model. The study will look at how the correlation matrix of the factors in the model can be updated in order to obtain as little variation as possible for the estimate of the economic capital. Four major approaches will be conducted to try and minimize this variation. The approaches use techniques such as weighting of consecutive correlation matrices, bootstrapping and standardization of the data using a multivariate CCC GARCH model.}, author = {Tellqvist, Ella and Kustvall Larsson, Martin}, language = {eng}, note = {Student Paper}, title = {Robustness Analysis when Estimating Economic Capital for Credit Risk}, year = {2016}, }