Journal of the ACM (JACM)
Universal Portfolios With and Without Transaction Costs
Machine Learning - Special issue: computational learning theory, COLT '97
Universal portfolios with side information
IEEE Transactions on Information Theory
Approximation algorithms for restless bandit problems
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Approximation algorithms for restless bandit problems
Journal of the ACM (JACM)
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We examine a Markovian model for the price evolution of a stock, in which the probability of local upward or downward movement is arbitrarily dependent on the current price itself (and perhaps some auxiliary state information). This model directly and considerably generalizes many of the most well-studied price evolution models in classical finance, including a variety of random walk, drift and diffusion models. Our main result is a “universally profitable” trading strategy — a single fixed strategy whose profitability competes with the optimal strategy (which knows all of the underlying parameters of the infinite and possibly nonstationary Markov process).