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A Risk-Reward Framework for the Competitive Analysis of Adaptive Trading Strategies

Al-Binali, Sabah

Competitive analysis is concerned with minimizing a relative measure of performance. When applied to financial trading strategies, competitive analysis leads to the development of strategies with minimum relative performance risk. This approach is too inflexible. Many investors are interested in managing their risk:they may be willing to increase their risk for some form of reward. They may also have some forecast of the future. We propose to extend competitive analysis to provide a framework in which investors may develop trading strategies based on their risk tolerance and forecast. We introduce a new, nonstochastic, measure of the risk of an online algorithm, and a reward metric that is in the spirit of competitive analysis. We then show how investors can select a strategy that maximizes their reward should their forecast be correct, whilst still respecting their risk tolerance.

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Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-019-97
Published Here
April 25, 2011