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作者机构:Columbia Univ Dept Comp Sci New York NY 10027 USA
出 版 物:《ALGORITHMICA》 (算法)
年 卷 期:1999年第25卷第1期
页 面:99-115页
核心收录:
学科分类:08[工学] 0835[工学-软件工程] 0701[理学-数学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:adaptive trading strategies competitive analysis forecast on-line algorithms reward risk
摘 要: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. In this paper we extend competitive analysis to provide a framework in which investors can develop optimal trading strategies based on their risk tolerance and forecast. We first define notions of risk and reward that are natural extensions of classical competitive analysis and then illustrate our ideas using the ski-rental problem. Finally, we analyze a financial game using the risk-reward framework, and, in particular, derive an optimal risk-tolerant algorithm.