Add to ORKGAbstract. Using an approach based on Bayesian inference, we propose a method to compute an estimate for the Value-at-Risk of an insurance loss ratio, taking both parameter and model risk into account
It is often necessary to estimate probability distributions to describe the loss processes covered b...
The management of operational risk in the banking industry has undergone explosive changes over the ...
When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for ...
MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･イ...
In order to quantify the operational risk capital charge under the current regulatory framework for ...
One of the main problems in risk management is the lack of loss data, which affects the parameter es...
One of the main problems in operational risk management is the lack of loss data, which affects the ...
One of the main problems in operational risk management is the lack of loss data, which affects the ...
Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and em...
We consider the problem of determining health insurance premiums based on past information on size o...
This paper will discuss a proposed method for the estimation of loss distribution using information ...
In order to measure hedge funds operating under the wings of two documented, many financial institut...
Operational risk is defined as a risk causing loss to investors resulting from inadequate processes,...
The derivation of loss distribution from insurance data is a very interesting research topic but at ...
In this paper we construct a stochastic model and derive approximation formulae to estimate the stan...
It is often necessary to estimate probability distributions to describe the loss processes covered b...
The management of operational risk in the banking industry has undergone explosive changes over the ...
When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for ...
MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･イ...
In order to quantify the operational risk capital charge under the current regulatory framework for ...
One of the main problems in risk management is the lack of loss data, which affects the parameter es...
One of the main problems in operational risk management is the lack of loss data, which affects the ...
One of the main problems in operational risk management is the lack of loss data, which affects the ...
Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and em...
We consider the problem of determining health insurance premiums based on past information on size o...
This paper will discuss a proposed method for the estimation of loss distribution using information ...
In order to measure hedge funds operating under the wings of two documented, many financial institut...
Operational risk is defined as a risk causing loss to investors resulting from inadequate processes,...
The derivation of loss distribution from insurance data is a very interesting research topic but at ...
In this paper we construct a stochastic model and derive approximation formulae to estimate the stan...
It is often necessary to estimate probability distributions to describe the loss processes covered b...
The management of operational risk in the banking industry has undergone explosive changes over the ...
When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for ...