This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both linear and non-linear portfolios. The Bayesian approach provides risk traders with the flexibility of adjusting their VaR models according to their subjective views. First, we deal with the case of linear portfolios. By imposing the conjugate-prior assumptions, a closed-form expression for the Bayesian VaR is obtained. The Bayesian VaR model can also be adjusted in order to deal with the ageing effect of the past data. By adopting Gerber-Shiu's option-pricing model, our Bayesian VaR model can also be applied to deal with non-linear portfolios of derivatives. We obtain an exact formula for the Bayesian VaR in the case of a single European call op...
We propose a new Unconditional Coverage backtest for VaR-forecasts under a Bayesian framework that s...
Mean-variance efficient portfolio analysis is applied to situations where not all assets are perfect...
Value at Risk (VaR) is one of the most popular tools used to estimate exposure to market risks, and ...
This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both lin...
This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both lin...
This thesis concerns portfolio theory from a Bayesian perspective and it includes two papers related...
The s-period ahead Value-at-Risk (VaR) for a portfolio of dimension n is considered and its Bayesian...
The s-period ahead Value-at-Risk (VaR) for a portfolio of dimension n is considered and its Bayesian...
We study the optimal portfolio allocation problem from a Bayesian perspective using value at risk (V...
When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for ...
AbstractThis paper proposes a novel nonlinear model for calculating Value-at-Risk (VaR) when the mar...
With the continuous development of the financial industry, financial risk management is increasingly...
This study assesses the accuracy of the value-at-risk estimate (VaR). On the basis of posterior dis...
It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institu...
A new extreme value mixture modelling approach for estimating Value-at-Risk (VaR) is proposed, overc...
We propose a new Unconditional Coverage backtest for VaR-forecasts under a Bayesian framework that s...
Mean-variance efficient portfolio analysis is applied to situations where not all assets are perfect...
Value at Risk (VaR) is one of the most popular tools used to estimate exposure to market risks, and ...
This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both lin...
This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both lin...
This thesis concerns portfolio theory from a Bayesian perspective and it includes two papers related...
The s-period ahead Value-at-Risk (VaR) for a portfolio of dimension n is considered and its Bayesian...
The s-period ahead Value-at-Risk (VaR) for a portfolio of dimension n is considered and its Bayesian...
We study the optimal portfolio allocation problem from a Bayesian perspective using value at risk (V...
When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for ...
AbstractThis paper proposes a novel nonlinear model for calculating Value-at-Risk (VaR) when the mar...
With the continuous development of the financial industry, financial risk management is increasingly...
This study assesses the accuracy of the value-at-risk estimate (VaR). On the basis of posterior dis...
It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institu...
A new extreme value mixture modelling approach for estimating Value-at-Risk (VaR) is proposed, overc...
We propose a new Unconditional Coverage backtest for VaR-forecasts under a Bayesian framework that s...
Mean-variance efficient portfolio analysis is applied to situations where not all assets are perfect...
Value at Risk (VaR) is one of the most popular tools used to estimate exposure to market risks, and ...