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Published in:
2010 | OriginalPaper | Chapter
Switching Investments
Authors : Wouter M. Koolen, Steven de Rooij
Published in: Algorithmic Learning Theory
Publisher: Springer Berlin Heidelberg
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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
(
T
2
) 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.