Optimal long term investment model with memory

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We consider a financial market model driven by an R^n-valued Gaussian process with stationary increments which is different from Brownian motion. This driving noise process consists of $n$ independent components, and each component has memory described by two parameters. For this market model, we explicitly solve optimal investment problems. These include (i) Merton's portfolio optimization problem; (ii) the maximization of growth rate of expected utility of wealth over the infinite horizon; (iii) the maximization of the large deviation probability that the wealth grows at a higher rate than a given benchmark. The estimation of paremeters is also considered.
25 pages, 3 figures. To appear in Applied Mathematics and Optimization

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Probability, Portfolio Management, MSC-class: 91B28, 60G10 (Primary) 62P05, 93E20 (Secondary)

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http://salesiana.dossiersoluciones.com/handle/123456789/208909

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/math/0506621
 http://arxiv.org/abs/math/0506621

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arXiv