Growth optimal portfolio selection strategies with transaction costs
Laszlo Gyorfi and István Vajda
19th International Conference on Algorithmic Learning Theory, ALT 2008, Proceedings
Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence
, Berlin, Heidelberg, Germany
Discrete time infinite horizon growth optimal investment in stock markets with transaction costs is considered. The stock processes are modelled by homogeneous Markov processes. Assuming that the distribution of the market process is known, we show two recursive investment strategies such that, in the long run, the growth rate on trajectories (in "liminf" sense) is greater than or equal to the growth rate of any other investment strategy with probability 1.