A probabilistic risk-to-reward measure for evaluating the performance of financial securities

P. Maguire, Philippe Moser, J. McDonnell, R. Kelly, Simon Fuller, R. Maguire
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引用次数: 3

Abstract

Existing risk-to-reward measures, such as the Sharpe ratio [1] or M2 [2], are based on the idea of quantifying the excess return per unit of deviation in an investment. In this preliminary article we introduce a new probabilistic measure for evaluating investment performance. Randomness Deficiency Coefficient (RDC) expresses the likelihood that the observed excess return of an investment has been generated by chance. Some of the advantages of RDC over existing measures are that it can be used with small historical datasets, is time-frame independent, and can be easily adjusted to take into account the familywise error rate which results from selection bias. We argue that RDC captures the fundamental relationship between risk and reward and prove that it converges with Sharpe's ratio.
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一种评估金融证券表现的概率风险回报度量
现有的风险回报指标,如夏普比率[1]或M2[2],都是基于量化投资中每单位偏差的超额回报的想法。在这篇初步的文章中,我们引入了一种新的评估投资绩效的概率度量。随机缺陷系数(RDC)表示观察到的超额投资收益是偶然产生的可能性。相对于现有的测量方法,RDC的一些优点是它可以用于小型历史数据集,与时间框架无关,并且可以很容易地调整以考虑由选择偏差导致的家庭误差率。我们认为RDC抓住了风险与回报之间的基本关系,并证明了它收敛于夏普比率。
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