Bayesian learning ; Dynamic decision making ; Futures contracts ; Bellman function
Subject RIV
BB - Applied Statistics, Operational Research
R&D Projects
2C06001 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
GA102/08/0567 GA ČR - Czech Science Foundation (CSF)
CEZ
AV0Z10750506 - UTIA-B (2005-2011)
Annotation
This research report is closely connected to the long time running research of the usage of the theory of Bayesian learning, stochastic dynamic programming and its approximations in futures dealing problem. This report describes tuning of one selectable parameter, which occurs in the new-designed algortihm called iterations-spread-in-time strategy. Experiment is done on real economic data on 35 selected futures markets. The main criterion of succes is the so-called net profit and also comparison with the previous experiments.
