首页> 外文期刊>Journal of statistical computation and simulation >European call price modelling using neural networks in considering volatility as stochastic with comparison to the Heston model
【24h】

European call price modelling using neural networks in considering volatility as stochastic with comparison to the Heston model

机译:欧洲呼叫价格建模使用神经网络考虑波动性与Heston模型相比

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

The aim of this paper is to model the European call price using neural networks (NNs). Many existing works have treated the problem as Hutchinson et al. [(1994). A nonparametric approach to pricing and hedging derivative securities via learning networks. J Finance. 49(3):851-889] Compared to these previous studies, the originality of our work consists in considering the volatility as stochastic and then to compare the NN's results to those of Heston (1993) model rather than to those of Black and Scholes [(1973 May-Jun). The pricing of options and corporate liabilities. J Polit Econ. 81(3):637-654)] as Hutchinson et al. did. We base our empirical work on real data (12 contracts on CAC40 index from the period January 2005 to January 2007). We found that the NNs approach gives better performances than the Heston's, in terms of accuracy and convergence speed.
机译:本文的目的是使用神经网络(NNS)来模拟欧洲呼叫价格。许多现有的作品已经将问题视为Hutchinson等人。 [(1994)。通过学习网络对定价和对冲衍生证券的非参数方法。 j金融。 49(3):851-889]与以前的研究相比,我们工作的原创性在于将波动性视为随机,然后将NN的结果与哈斯顿(1993)模型的结果进行比较,而不是对黑人和学术人员的结果[(1973年5月)。选项和企业负债定价。 J PORIT ECON。 81(3):637-654)]作为Hutchinson等人。做过。我们将我们的实证工作基于实际数据(从2005年1月期间为CAC40指数的12个合同,从2005年1月至2007年1月)。我们发现,在准确性和收敛速度方面,NNS的方法比HESTON提供更好的表现。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号