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文章基本信息

  • 标题:Distributional Approximation of Asset Returns with Nonparametric Markovian Trees
  • 本地全文:下载
  • 作者:Gaetano Iaquinta ; Sergio Ortobelli,Lozza
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2006
  • 卷号:6
  • 期号:11
  • 页码:69-74
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The paper proposes the use a Markov chain to model and predict the distributional behaviour of a portfolio of returns. In particular, it describes an algorithm to compute the distribution of returns that follow a markovian tree. This approach reduces the computational complexity as compared to the classic markovian approach, since the tree recombines at each temporal step. Furthermore, the paper compares ex-post the assumption that returns follow either a geometric Brownian motion or a Markov chain. Finally, it discusses some possible financial applications of the proposed approach.
  • 关键词:Computational complexity, Markov chain, return distribution, financial applications.
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