Localized Conditional Autoregressive Expectile Model

Speaker(s): 
Xiu Xu (Humboldt-Unverisität zu Berlin)
Date: 
Monday, June 15, 2015 - 2:00pm
Location: 
Spandauer Straße 1, Room 23

Localized conditional autoregressive expectile (CARE) model accounts for time-varying parameters in tail risk modelling. Our technique strikes a balance between parameter variability and the modelling bias resulting in potentially varying parameter homogeneity interval lengths. Over this intervals one can safely assume a parametric model in expectile estimation. Based on empirical evidence at three stock markets between 2005-2014 we show that CARE parameters vary over time and exhibit changing distributional properties. It is recommended to use between 1 month and 1 year of data in expectile modelling at any trading day.