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16

NIPS
2003

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Can We Learn to Beat the Best Stock

13 years 5 months ago

Can We Learn to Beat the Best Stock

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A novel algorithm for actively trading stocks is presented. While traditional universal algorithms (and technical trading heuristics) attempt to predict winners or trends, our approach relies on predictable statistical relations between all pairs of stocks in the market. Our empirical results on historical markets provide strong evidence that this type of technical trading can “beat the market” and moreover, can beat the best stock in the market. In doing so we utilize a new idea for smoothing critical parameters in the context of expert learning.

Allan Borodin, Ran El-Yaniv, Vincent Gogan

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	NIPS
Authors	Allan Borodin, Ran El-Yaniv, Vincent Gogan

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