Quantile methods for complex financial systems

This project aims to provide innovative techniques to estimate and predict moderate and extreme tail risk in complex financial systems more effectively. This is of key interest to both market participants and also prudential supervisors. The focus on econometric methodologies for conditional quantiles and expectiles is directly related to the Value-at-Risk (VaR) concept of risk measurement, however, all approaches presented are readily extendible to further risk measures such as, expected shortfall.

Principal Investigators
Wang, Weining Prof. Dr. (Details) (Nonparametric Statistics and Dynamic Risk Management)

Duration of Project
Start date: 10/2016
End date: 09/2019

Last updated on 2020-07-07 at 13:21