Discrete time market with serial correlations and optimal myopic strategies.
MetadataShow full item record
NOTICE: This is the author's version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was sumitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 177, 2, 2007. DOI: 10.1016/j.ejor.2006.01.004
The paper studies discrete time market models with serial correlations. We found a market structure that ensures that the optimal strategy is myopic for the case of both power or logutility function. In addition, discrete time approximation of optimal continuous time strategies for diffusion market is analyzed. It is found that the performance of optimal myopic diffusion strategies cannot be approximated by optimal strategies with discrete time transactions that are optimal for the related discrete time market model.
Showing items related by title, author, creator and subject.
Rodkina, A.; Dokuchaev, Nikolai (2015)This paper studies the properties of discrete-time stochastic optimal control problems associated with portfolio selection. We investigate if optimal continuous-time strategies can be used effectively for a discrete-time ...
Woon, Siew Fang (2009)Optimal control problems arise in many applications, such as in economics, finance, process engineering, and robotics. Some optimal control problems involve a control which takes values from a discrete set. These problems ...
Optimal Control Computation for Discrete Time Time-Delayed Optimal Control Problem with All-Time-Step Inequality ConstraintsLi, Bin; Teo, Kok Lay; Duan, G. (2010)In this paper, we consider a class of discrete time optimal control problems with time delay and subject to nonlinear all-time-step inequality constraints on both the state and control. By using a constraint transcription ...