A range of statistical models for the joint distribution of different financial market returns has been developed. The statistical property of interest is the tail behaviour of these models and their abilities to capture features of extreme events in the financial markets, such as sharp falls in one or multiple markets within a short period of time. A conditional approach based on multivariate extreme value theory is considered and compared to a few other benchmark models commonly used in the industry. The conditional approach is extended to have hierarchically structured parameters with the aim to incorporate the underlying financial market factors. Analysis based on both simulated and empirical data shows that the proposed approaches are ...
Although stock prices fluctuate, the variations are relatively small and are frequently assumed to b...
This paper presents extreme value theory and its application to the computation of the value at risk...
We compare the traditional GARCH models with a semiparametric approach based on extreme value theory...
This paper presents a model for the joint distribution of a portfolio by inferring extreme movements...
One of the key components of financial risk management is risk measurement. This typically requires ...
This article presents a general framework for identifying and modeling the joint-tail distribution b...
This article presents a general framework for identifying and modeling the joint-tail distribution b...
This paper develops a new class of dynamic models for forecasting extreme financial risk. This class...
This paper develops an unconditional and conditional extreme value approach to calculating value at ...
The project focuses on the estimation of the probability distribution of a bivariate random vector g...
The ability to model extreme events is important across many applications, including extreme weather...
This article reviews methods from extreme value analysis with applications to risk assessment in fin...
Accurate forecasting of risk is the key to successful risk management techniques. Using the largest...
The phenomenon of the occurrence of rare yet extreme events, “Black Swans ” in Taleb’s ter-minology,...
This paper conducts a comparative evaluation of the predictive performance of various Value-at-Risk ...
Although stock prices fluctuate, the variations are relatively small and are frequently assumed to b...
This paper presents extreme value theory and its application to the computation of the value at risk...
We compare the traditional GARCH models with a semiparametric approach based on extreme value theory...
This paper presents a model for the joint distribution of a portfolio by inferring extreme movements...
One of the key components of financial risk management is risk measurement. This typically requires ...
This article presents a general framework for identifying and modeling the joint-tail distribution b...
This article presents a general framework for identifying and modeling the joint-tail distribution b...
This paper develops a new class of dynamic models for forecasting extreme financial risk. This class...
This paper develops an unconditional and conditional extreme value approach to calculating value at ...
The project focuses on the estimation of the probability distribution of a bivariate random vector g...
The ability to model extreme events is important across many applications, including extreme weather...
This article reviews methods from extreme value analysis with applications to risk assessment in fin...
Accurate forecasting of risk is the key to successful risk management techniques. Using the largest...
The phenomenon of the occurrence of rare yet extreme events, “Black Swans ” in Taleb’s ter-minology,...
This paper conducts a comparative evaluation of the predictive performance of various Value-at-Risk ...
Although stock prices fluctuate, the variations are relatively small and are frequently assumed to b...
This paper presents extreme value theory and its application to the computation of the value at risk...
We compare the traditional GARCH models with a semiparametric approach based on extreme value theory...