Portfolio selection with transaction costs
Mathematics of Operations Research
COLT '90 Proceedings of the third annual workshop on Computational learning theory
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
A randomization rule for selecting forecasts
Operations Research
A game of prediction with expert advice
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
A comparison of new and old algorithms for a mixture estimation problem
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Universal data compression and portfolio selection
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
EXPONENTIATED GRADIENT VERSUS GRADIENT DESCENT FOR LINEAR PREDICTORS
EXPONENTIATED GRADIENT VERSUS GRADIENT DESCENT FOR LINEAR PREDICTORS
TIGHT WORST-CASE LOSS BOUNDS FOR PREDICTING WITH EXPERT ADVICE
TIGHT WORST-CASE LOSS BOUNDS FOR PREDICTING WITH EXPERT ADVICE
Learning probabilistic prediction functions
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
Universal portfolios with side information
IEEE Transactions on Information Theory
Fast Universalization of Investment Strategies with Provably Good Relative Returns
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Efficient algorithms for universal portfolios
The Journal of Machine Learning Research
Internal Regret in On-Line Portfolio Selection
Machine Learning
Algorithms for portfolio management based on the Newton method
ICML '06 Proceedings of the 23rd international conference on Machine learning
Online Markov Decision Processes
Mathematics of Operations Research
IEEE Transactions on Signal Processing
Factor graphs for universal portfolios
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
CORN: Correlation-driven nonparametric learning approach for portfolio selection
ACM Transactions on Intelligent Systems and Technology (TIST)
Regret minimization algorithms for pricing lookback options
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Pricing exotic derivatives using regret minimization
SAGT'11 Proceedings of the 4th international conference on Algorithmic game theory
Trading in markovian price models
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Competitive strategy for on-line leasing of depreciable equipment
Mathematical and Computer Modelling: An International Journal
Confidence Weighted Mean Reversion Strategy for Online Portfolio Selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Online portfolio selection: A survey
ACM Computing Surveys (CSUR)
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A constant rebalanced portfolio is an investment strategy which keepsthe same distribution of wealth among a set of stocks from period to period.Recently there has been work on on-line investment strategies thatare competitive with the best constant rebalanced portfolio determinedin hindsight (Cover, 1991, 1996; Helmbold et al., 1996; Cover & Ordentlich, 1996a, 1996b; Ordentlich & Cover, 1996). For the universal algorithm of Cover (Cover, 1991),we provide a simple analysis which naturallyextends to the case of a fixed percentage transaction cost (commission ), answering a question raised in (Cover, 1991; Helmbold et al., 1996; Cover & Ordentlich, 1996a, 1996b; Ordentlich & Cover, 1996; Cover, 1996). In addition, we present a simple randomized implementation that is significantly faster in practice. We conclude by explaining how these algorithms can be applied to other problems, such as combining the predictions of statistical language models, where the resulting guarantees are more striking.