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Robustness Analysis when Estimating Economic Capital for Credit Risk

Tellqvist, Ella and Kustvall Larsson, Martin (2016) FMS820 20161
Mathematical 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 multi-factor 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)
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author
Tellqvist, Ella and Kustvall Larsson, Martin
supervisor
organization
course
FMS820 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8891072
date added to LUP
2016-09-07 15:14:37
date last changed
2016-09-07 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 multi-factor 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},
}