期刊文献+

一种考虑基差非对称影响的期货波动性预测模型研究——基于上海铜期货市场的实证分析 被引量:4

A Forecasting Model for Evaluating the Asymmetric Impacts on the Basis of the Volatility of Futures
下载PDF
导出
摘要 研究了基差对上海铜期货收益波动率影响的非对称效应。实证结果表明,基差对铜期货的收益波动存在显著的非对称影响,其中负基差对波动性的影响要明显大于正的基差项。通过与GARCH模型和未考虑基差项的SE-GARCH模型对铜期货的样本外预测能力的比较表明,考虑基差对波动性的非对称影响的AE-GARCH模型能显著地减小铜期货波动性预测的误差。 This paper discusses the asymmetric impacts on the basis on the volatility of Shanghai copper futures. The results of the empirical study suggests that the asymmetric effect is significant. The negative basis impacts the volatility more significant than the positive basis does. The out-sample contrasts show that forecasting the copper volatility evaluating the asymmetric effects can reduce the forecasting error and improve the forecast effects.
出处 《北京理工大学学报(社会科学版)》 CSSCI 2008年第4期27-30,共4页 Journal of Beijing Institute of Technology:Social Sciences Edition
关键词 期货 基差 非对称效应 预测 futures basis asymmetric effects forecast
  • 相关文献

参考文献7

  • 1李亚静,朱宏泉,彭育威.基于GARCH模型族的中国股市波动性预测[J].数学的实践与认识,2003,33(11):65-71. 被引量:47
  • 2郑梅,苗佳,王升.预测沪深股市市场波动性[J].系统工程理论与实践,2005,25(11):41-45. 被引量:21
  • 3庞素琳,徐建闽,黎荣舟.BP算法和对称ARCH类模型对股市波动性预测的实证比较[J].控制理论与应用,2006,23(4):658-662. 被引量:6
  • 4Lee T H. Spread and volatility in spot and forward exchange rates[J]. Journal of International Money and Finance, 1994, 13:375 - 383.
  • 5Zhong M, Darrat A F, Otero R. Price discovery and volatility spillovers in index futures markets: Some evidence from Mexico[J]. Journal of Banking and Finance, 2004, 28:3037-3054.
  • 6Donald Lien, Li Yang. Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets[J]. Journal of Banking & Finance, 2007,1:1-12.
  • 7Kroner K F, Sultan J.Time varying distribution and dynamic hedging with foreign currency futures. J. Financ. Quant. Anal[J]. 1993,28:535-551.

二级参考文献13

  • 1陈岱孙.计量经济学[M].北京:中国人民大学出版社,2000.427.
  • 2Hentschel L. All in the family: Nesting symmetric and asymmetric GARCH models[ J]. Journal of Financial Economics, 1995, 39:71 - 104.
  • 3Engle R F.Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation[J].Economitrica,1982,50:987-1008.
  • 4Bollerslev T.Generalized autoregressive conditional heteroskedasticity[J].J of Economitrics,1986,31:307-327.
  • 5Akgiray V.Conditional heteroskedasticity in time series of stock returns:Evidence and forecasts[J].J of Business,1989,62:55-80.
  • 6Bernd F,Klaus R.Volatility estimation with neural network[C] //Proc of IEEE/IAFE Conf on Computational Intelligence for Financial Engineering,1996.New York,USA:[s.n.],1996:177-181.
  • 7Donaldson,Kamstra.Neural network forecast combining with interaction effects[J].J of Franklin Institute,1999,336:227-236.
  • 8QI Min,ZHANG Guoqiang.An investigation of model selection criteria for neural network time series forecasting[J].European J of Operational Research,2001,132:666-680.
  • 9PANG Sulin.An application of logistic model in stock forecasting[C]//Proc of the Eighth Int Conf on Control Automation,Robotics and Vision.[s.1.]:[s.n.],2004:1491-1496.
  • 10刘新勇,贺江峰,孟祥泽,陈增强,袁著祉.基于神经网络的股市预测[J].南开大学学报(自然科学版),1998,31(3):39-44. 被引量:11

共引文献65

同被引文献40

引证文献4

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部