經濟與管理論叢(Journal of Economics and Management)  
  Volume 12, No. 1  
  February, 2016  
     
 

A Quantile Regression Approach to the Multiple

 
 

Period Value at Risk Estimation

 
   
  Chi Ming Wong  
 

School of Mathematical and Physical Sciences, University of Technology Sydney, Australia

 
   
  Lei Lam Olivia Ting  
  DBS Bank, Hong Kong SAR  
 

Abstract

 

This research focuses on methods for multiple period Value at Risk (VaR) estimation by utilizing some common approaches like RiskMetrics and empirical distribution and examining quantile regression. In a simulation study we compare the least square and quantile regression percentiles with the actual percentiles for different error distributions. We also discuss the method of selecting response and explanatory variables for the quantile regression approach. In an empirical study, we apply the three VaR estimation approaches to the aggregate returns of four major market indices. The results indicate that the quantile regression approach is better than the other two approaches.

   

 

 

Keywords: quantile regression, value at risk, risk measures

 

 

JEL classification: C530, C580, G170

 

 
   

 

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