Markov Decision Programming Model for Stock Investment
Kang Jian-lin · Journal of China University of Mining and Technology · 2005
By applying the Markov decision programming theory, a dynamic investment strategy for stocks was discussed. The stochastic time series of stock price was decomposed into the sum of tendency series and residual series. And it was proved that the latter has a Markov property, as a result, a model for investment decision was established. The theorem proposed showed that the optimal investment strategy of the target function exists under certain condition. In addition, an algorithm to seek optimal strategy and an example of two stages were given. The feasibility of this investment decision model was proved by some practical examples.