4 papers
High dimensional inference for extreme value indices
Liujun Chen, Chen Zhou
When applying multivariate extreme value statistics to analyze tail risk in compound events defined by a multivariate random vector, one often assumes that all dimensions share the…
High Dimensional Mean Test for Shrinking Random Variables with Applications to Backtesting
Liujun Chen, Chen Zhou
We propose a high dimensional mean test framework for shrinking random variables, where the underlying random variables shrink to zero as the sample size increases. By pooling obse…
Clustering Tails in High Dimension
Liujun Chen, Marco Oesting, Chen Zhou
One potential solution to combat the scarcity of tail observations in extreme value analysis is to integrate information from multiple datasets sharing similar tail properties, for…
Max-Linear Tail Regression
Liujun Chen, Deyuan Li, Zhengjun Zhang
The relationship between a response variable and its covariates can vary significantly, especially in scenarios where covariates take on extremely high or low values. This paper in…