Výzkumná zpráva

Slimáček V., Zeman J., Kárný M.

Research Report

2227

ÚTIA AV ČR

Praha

2008

Ing. Miroslav Kárný, DrSc. (ÚTIA - Oddělení adaptivních systémů)

dynamic decision making, stochastic dynamic programming, Bay

This work deals with dynamic decision making via approximate dynamic programming in application to the futures trading. This work describes the theoretical description of dynamic decision making and approximate dynamic programming, you can also nd here the principles of Bayesian estimation, which is necessary for solving our task.We designed and described one of possible trading strategy { receding horizont strategy combined with anticipative strategy, the predictions of prices, which are necessary for using of this strategy, are made by certainty equivalence strategy and by Monte Carlo method. The designed strategy was tested on real data and unfortunately this strategy doesn t provide a prot.