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

  • Xiufang Chen
  • Chaoping Zhang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 227)


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.




  1. 1.
    Wang X, Shi DJ (2001) Extreme value statistical theory and its application in financial risk. J Quant Tech Econ 18(8):109–111Google Scholar
  2. 2.
    Ouyang ZS, Gong SM (2005) GPD model as a risk management tool. Theor Pract Finan Econ 26(6):88–92Google Scholar
  3. 3.
    Chen XF, Chen GB (2012) Pattern search for generalized hyperbolic distribution and financial risk measure. Appl Mech Mater, doi: 10.4028/ 42(4):155–156Google Scholar
  4. 4.
    Tian XS, Mao HY (2003) Estimation of value-at-risk based on POT model. J Huazhong Univ Sci Technol (Soc Sci Ed) 17(11):97–100Google Scholar
  5. 5.
    Gao S, Lin L, Shi DJ (2004) The pot model for the stationary sequence and its application in computing value-at-risk of exchange rates. Syst Eng 22(2):49–53Google Scholar
  6. 6.
    Hua YJ (2011) Study on extreme value theory and its application in risk measurement of Shanghai and Shenzhen stock markers, vol 37(6). Science Press, Beijing, pp 27–30Google Scholar

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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