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Chinese Journal of Management Science ›› 2015, Vol. 23 ›› Issue (6): 32-40.doi: 10.16381/j.cnki.issn1003-207x.201.06.005

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The Shanghai Stock Index Volatility:Forecasting Research Based on Fuzzy FEGARCH Model and Different Distribution Hypothesis

HOU Li-qiang, YANG Shan-lin, WANG Xiao-jia, CHEN Zhi-qiang   

  1. School of Management of Hefei University of Technology, Hefei 230009, Ching
  • Received:2013-07-15 Revised:2014-02-21 Online:2015-06-20 Published:2015-07-22

Abstract: In general, the transmission of volatility in the stock market is time-varying, nonlinear, and asymmetric with respect to both positive and negative results. Given this fact, the method of fuzzy logic systems is adopted to modify the threshold values for an EGARCH model.The volatility forecasting for the SSEC stock index series from 2006 to 2011 is provided and the essential source of performance improvements is identified between distributional assumption and volatility specification suing distribution-type (GARCH-N,GARCH-t,GARCH-HT and GARCH-SGT)and asymmetry-type(GJR-GARCH and EGARCH) volatility models through the superior predictive ability test. Such evidence strongly demonstrates that modeling asymmetric components which is the fuzzy EGARCH model is more important than specifying error distribution for improving volatility forecasts of financial returns in the presence of fat-tails,leptokurtosis, skewness, leverage effects and nonlinear effects in china stock market.

Key words: volatility, fuzzy EGARCH test model, forecasting, superior predictive ability

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