CMStatistics 2020: Start Registration
View Submission - CMStatistics
Title: Proxy variables to common factors and parameter estimation in factor copula models Authors:  Pavel Krupskiy - Melbourne University (Australia) [presenting]
Harry Joe - University of British Columbia (Canada)
Abstract: Factor copula models assume observed variables are independent conditional on one or several unobserved factors. We show that, under some mild assumptions, proxy variables to the unobserved factors can be obtained from the observed variables when the dimension is large. These proxy variables can help to select appropriate linking copulas in some factor copula models and to perform numerically faster maximum likelihood estimation of parameters of these high-dimensional copulas. A simulation study shows that parameter estimates obtained using the proxy variable approach are close to those obtained using the maximum likelihood approach. The proxy variable approach is used to analyze a financial data set of stock returns from different sectors.