COLT 2005: Learning Theory pp 606-620 | Cite as

Trading in Markovian Price Models

  • Sham M. Kakade
  • Michael Kearns
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3559)

Abstract

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).

Keywords

Random Walk Trading Strategy Competitive Ratio Price Dynamic Price Movement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sham M. Kakade
    • 1
  • Michael Kearns
    • 1
  1. 1.Department of Computer and Information ScienceUniversity of PennsylvaniaPhiladelphia

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