文章基本信息

标题：Distributional Approximation of Asset Returns with Nonparametric Markovian Trees
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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.