Discrete-time log-optimal portfolio rebalancing: A scalable efficient algorithm

Portfolio rebalancing decisions are crucial to today´s portfolio managers especially in high frequency trading environment. These decisions must be made fast in dynamic market conditions. We analyze the efficiency and scalability of a proposed discrete-time rebalancing algorithm suitable for log-optimal investors. These investors seek to maximize the expected value of log of portfolio growth in the long run. We incrementally utilize various computational and optimization techniques to develop a highly efficient version of the algorithm.