Switching investments

  • Authors:
  • Wouter M. Koolen;Steven de Rooij

  • Affiliations:
  • Centrum Wiskunde en Informatica, Amsterdam;Statistical Laboratory, DPMMS, Cambridge, UK

  • Venue:
  • ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
  • Year:
  • 2010
  • Buy low, sell high

    ALT'12 Proceedings of the 23rd international conference on Algorithmic Learning Theory

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Abstract

We present a simple online two-way trading algorithm that exploits fluctuations in the unit price of an asset. Rather than analysing worst-case performance under some assumptions, we prove a novel, unconditional performance bound that is parameterised either by the actual dynamics of the price of the asset, or by a simplifying model thereof. The algorithm processes T prices in O(T2) time and O(T) space, but if the employed prior density is exponential, the time requirement reduces to O(T). The result translates to the prediction with expert advice framework, and has applications in data compression and hypothesis testing.