Time-Varying Mixture Models for Financial Risk Management

• Activity Number: 141
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Risk Analysis
• Author(s): Shuguang Zhang* and Xufeng Niu
• Companies: Florida State University and Florida State University
• Keywords: Risk Analysis ; Mixture Model ; Value At Risk ; Time Series

Abstract

Motivated by understanding the devastating financial crisis in 2008 that was partially caused by underestimation of financial risk, we propose a class of time-varying mixture models for risk analysis and management. Previously one commonly used approach to estimate VaR is the Variance-Covariance method, in which normal distribution is usually assumed for asset returns that may underestimate the real risk. To address this issue, we will use time-varying mixture models of distributions from different families for the estimation of VaR, in which weights for each distribution at different time periods will be estimated based on macroeconomic indices. In addition, time series models will be used to examine the correlation structure of the time-varying weights. Statistical properties of the models will be investigated, including estimation methods and asymptotic results of the parameter estimates. Simulation study will be carried out to evaluate different estimation methods and model selection procedures.