Universal portfolios with and without transaction costs
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Universal Portfolios With and Without Transaction Costs
Machine Learning - Special issue: computational learning theory, COLT '97
Efficient algorithms for universal portfolios
The Journal of Machine Learning Research
Online portfolio selection: A survey
ACM Computing Surveys (CSUR)
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The authors consider universal data compression, universal portfolio selection (online portfolio algorithms) and the relationship of both to information theory. Apparently the fundamental minimax redundancy game in data compression and the minimax regret game for the growth rate of wealth in investment have the same answer. There is also a duality between entropy rate and the growth rate of wealth.