Risk Measure for Nonferrous Metals Futures Based on PSO-GARCH-GPD Model

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 227)

Abstract

To estimate value at risk (VaR) and conditional value at risk (CVaR) of nonferrous metals futures, this study estimates the shape parameter and scale parameter in peaks over threshold model (POT) model by particle swarm optimization algorithm (PSO). Hill plot and mean excess function (MEF) plot together determine the appropriate thresholds of POT model for different nonferrous metals futures. The volatility of the return is computed respectively by generalized Pareto distribution (GPD) model and GARCH-GPD model. The results show that VaR and CVaR based on PSO-GARCH-GPD are effective to measure the risks of nonferrous metals futures.

Keywords

PSO GPD GARCH VaR CVaR 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.College of Electrical and Electronic EngineeringWuhan Polytechnic UniversityWuhanChina
  2. 2.Department of Physical and Electronic EngineeringLeshan Normal UniversityLeshanChina

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